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Awesome-RAG
💡 List of recent developments in Retrieval-Augmented Generation (RAG) for large language models (LLM).
🤗 We welcome and encourage researchers to submit pull requests to update information in their papers!
📫 _Repo under active development. Collaborations welcome on **Framework** & **Survey**. Contact: jiangyijcx@163.com._
## 📕 Overview
### [📌 Accepted papers](#Accept)
| | | | | |
|---------------------------|----------------------------|------------------------------|--------------------------|---------------------------|
| NIPS 2025 | EMNLP 2025 | [ACL 2025](#ACL-2025) | [ICML 2025](#ICML-2025) | [ICLR 2025](#ICLR-2025) |
| [NIPS 2024](#NIPS-2024) | [EMNLP 2024](#EMNLP-2024) | [ACL 2024](#ACL-2024) | [ICML 2024](#ICML-2024) | [ICLR 2024](#ICLR-2024) |
### [🗓️ 2026 papers](#2026)
| | | | | | |
|---------------------------------|---------------------------------|---------------------------------|---------------------------------|---------------------------------|---------------------------------|
| 2026.06 | 2026.05 | 2026.04 | [2026.03](#2026-March) | [2026.02](#2026-February) | [2026.01](#2026-January) |
### [🗓️ 2025 papers](#2025)
| | | | | | |
|---------------------------------|---------------------------------|---------------------------------|---------------------------------|---------------------------------|---------------------------------|
| [2025.12](#2025-December) | [2025.11](#2025-November) | [2025.10](#2025-October) | [2025.09](#2025-September) | [2025.08](#2025-August) |[2025.07](#2025-July) |
| [2025.06](#2025-June) | [2025.05](#2025-May) | [2025.04](#2025-April) | [2025.03](#2025-March) | [2025.02](#2025-February) | [2025.01](#2025-January) |
### [🗓️ 2024 papers](#2024)
| | | | | | |
|---------------------------------|---------------------------------|---------------------------------|-----------------------------------|-----------------------------------|-----------------------------------|
| [2024.12](#2024-December) | [2024.11](#2024-November) | [2024.10](#2024-October) | [2024.09](#2024-September) | [2024.08](#2024-August) |[2024.07](#2024-July) |
| [2024.06](#2024-June) | [2024 .05](#2024-May) | [2024.04](#2024-Apri) | [2024.03](#2024-March) | [2024.02](#2024-February) | [2024.01](#2024-January) |
### 🗃️ Evaluation Datasets
| | | | | | |
|---------------------------------|---------------------------------|---------------------------------|-----------------------------------|-----------------------------------|-----------------------------------|
| [HotpotQA](https://hotpotqa.github.io/) | [2WikiMultiHopQA](https://github.com/Alab-NII/2wikimultihop) | [WebQuestions](https://nlp.stanford.edu/software/sempre/) | [TriviaQA](http://nlp.cs.washington.edu/triviaqa/) | [MuSiQue](https://github.com/stonybrooknlp/musique) |[NaturalQA](https://ai.google.com/research/NaturalQuestions) |
| [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) | [PopQA](https://github.com/AlexTMallen/adaptive-retrieval) | [ASQA](https://github.com/google-research/language/tree/master/language/asqa) | [Bamboogle](https://huggingface.co/datasets/chiayewken/bamboogle) | [ARC_Challenge](http://data.allenai.org/arc) | [PubHealth](https://github.com/luohongyin/unilc) |
## 📢 Latest News
- **[26.04]:** Our **CoCoA** accepted at ***ACL2026 Main***! 🎉 [[Paper]](https://arxiv.org/pdf/2508.01696)[[Code]](https://github.com/liunian-Jay/CoCoA)
- **[26.1]:** Our [ArcAligner](https://arxiv.org/pdf/2601.05038) released — designed for long memory!🚀 [[Code]](https://github.com/liunian-Jay/ArcAligner)
- **[26.1]:** Our [OptiSet](https://arxiv.org/pdf/2601.05027) released — unified selection and ranking!🚀 [[Code]](https://github.com/liunian-Jay/OptiSet)
- **[25.10]:** Updated the recent papers from September and October!📅
- **[25.10]:** Our [QAgent](https://arxiv.org/pdf/2510.08383) released — an agentic RAG framework!🚀 [[Code]](https://github.com/LivingFutureLab/QAgent)
- **[25.08]:** Our [CoCoA](https://arxiv.org/pdf/2508.01696) released — studying knowledge synergy!🚀 [[Code]](https://github.com/liunian-Jay/CoCoA)
- **[25.06]:** We built [AgenticRAG-RL](https://github.com/liunian-Jay/AgenticRAG-RL) — a minimal RL-RAG! Feel free to contribute!🤝
- **[25.05]:** Our [GainRAG](https://arxiv.org/pdf/2505.18710) released — studying preference alignment!🚀 [[Code]](https://github.com/liunian-Jay/GainRAG)
- **[25.05]:** Our **GainRAG** accepted at ***ACL2025 Main***! 🎉 [[Paper]](https://arxiv.org/pdf/2505.18710)[[Code]](https://github.com/liunian-Jay/GainRAG)
- **[25.01-05]:** Updated the papers from 2025! 📄
- **[24.10]:** We built [MU-GOT](https://github.com/liunian-Jay/MU-GOT) — a PDF parsing tool! Feel free to contribute!🤝
- **[24.06-12]:** Updated the papers from 2024! 📄
### 🎁 Resources
#### 💡Survey
- [2025.05] A Survey on Knowledge-Oriented Retrieval-Augmented Generation [[Link]](https://arxiv.org/pdf/2503.10677)
- [2025.01] Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG [[Link]](https://arxiv.org/pdf/2501.09136)
- [2024.09] Trustworthiness in Retrieval-Augmented Generation Systems: A Survey [[Link]](https://arxiv.org/pdf/2409.10102?)
- [2024.09] Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely [[Link]](https://arxiv.org/pdf/2409.14924?)
- [2024.07] Retrieval-Augmented Generation for Natural Language Processing: A Survey [[Link]](https://arxiv.org/pdf/2407.13193?)
- [2024.05] A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models [[Link]](https://arxiv.org/pdf/2405.06211)
- [2024.02] Retrieval-Augmented Generation for AI-Generated Content: A Survey [[Link]](https://arxiv.org/pdf/2402.19473)
- [2023.12] Retrieval-Augmented Generation for Large Language Models: A Survey [[Link]](https://arxiv.org/pdf/2312.10997)
#### 💡Project
- [LightRAG](https://github.com/HKUDS/LightRAG)
- [RAGFlow](https://github.com/infiniflow/ragflow)
- [RAG-Anything](https://github.com/HKUDS/RAG-Anything)
- [Awesome-LLM-RAG](https://github.com/jxzhangjhu/Awesome-LLM-RAG)
## 🔥Latest Papers
### 🔥2026 March
- Mar 30 [PAR2-RAG: Planned Active Retrieval and Reasoning for Multi-Hop Question Answering](https://arxiv.org/pdf/2603.29085)
- Mar 30 [Courtroom-Style Multi-Agent Debate with Progressive RAG and Role-Switching for Controversial Claim Verification](https://arxiv.org/pdf/2603.28488)
- Mar 27 [Not All Entities are Created Equal: A Dynamic Anonymization Framework for Privacy-Preserving Retrieval-Augmented Generation](https://arxiv.org/pdf/2603.26074)
- Mar 27 [Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?](https://arxiv.org/pdf/2601.13227)
- Mar 26 [Adaptive Chunking: Optimizing Chunking-Method Selection for RAG](https://arxiv.org/pdf/2603.25333)
- March 26 [UniAI-GraphRAG: Synergizing Ontology-Guided Extraction, Multi-Dimensional Clustering, and Dual-Channel Fusion for Robust Multi-Hop Reasoning](https://arxiv.org/pdf/2603.25152)
- Mar 26 [GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem Structuring](https://arxiv.org/pdf/2603.26807)
- Mar 25 [Retrieval Improvements Do Not Guarantee Better Answers: A Study of RAG for AI Policy QA](https://arxiv.org/pdf/2603.24580)
- Mar 25 [CoCR-RAG: Enhancing Retrieval-Augmented Generation in Web Q&A via Concept-oriented Context Reconstruction](https://arxiv.org/pdf/2603.23989)
- Mar 24 [From Conflict to Consensus: Boosting Medical Reasoning via Multi-Round Agentic RAG](https://arxiv.org/pdf/2603.03292)
- Mar 23 [CatRAG: Functor-Guided Structural Debiasing with Retrieval Augmentation for Fair LLMs](https://arxiv.org/pdf/2603.21524)
- Mar 21 [Graphs RAG at Scale: Beyond Retrieval-Augmented Generation With Labeled Property Graphs and Resource Description Framework for Complex and Unknown Search Spaces](https://arxiv.org/pdf/2603.22340)
- Mar 19 [GIP-RAG: An Evidence-Grounded Retrieval-Augmented Framework for Interpretable Gene Interaction and Pathway Impact Analysis](https://arxiv.org/pdf/2603.20321)
- Mar 19 [BubbleRAG: Evidence-Driven Retrieval-Augmented Generation for Black-Box Knowledge Graphs](https://arxiv.org/pdf/2603.20309)
- Mar 19 [DaPT: A Dual-Path Framework for Multilingual Multi-hop Question Answering](https://arxiv.org/pdf/2603.19097)
- Mar 18 [PACE-RAG: Patient-Aware Contextual and Evidence-based Policy RAG for Clinical Drug Recommendation](https://arxiv.org/pdf/2603.17356)
- Mar 18 [SF-RAG: Structure-Fidelity Retrieval-Augmented Generation for Academic Question Answering](https://arxiv.org/pdf/2602.13647)
- Mar 17 [Is Conformal Factuality for RAG-based LLMs Robust? Novel Metrics and Systematic Insights](https://arxiv.org/abs/2603.16817)
- Mar 17 [IndexRAG: Bridging Facts for Cross-Document Reasoning at Index Time](https://arxiv.org/pdf/2603.16415)
- Mar 16 [Cross-RAG: Zero-Shot Retrieval-Augmented Time Series Forecasting via Cross-Attention](https://arxiv.org/pdf/2603.14709)
- Mar 14 [The Reasoning Bottleneck in Graph-RAG: Structured Prompting and Context Compression for Multi-Hop QA](https://arxiv.org/pdf/2603.14045)
- Mar 12 [Test-Time Strategies for More Efficient and Accurate Agentic RAG](https://arxiv.org/pdf/2603.12396)
- Mar 11 [RAGPerf: An End-to-End Benchmarking Framework for Retrieval-Augmented Generation Systems](https://arxiv.org/pdf/2603.10765)
- Mar 10 [TaSR-RAG: Taxonomy-guided Structured Reasoning for Retrieval-Augmented Generation](https://arxiv.org/pdf/2603.09341)
- Mar 9 [SPD-RAG: Sub-Agent Per Document Retrieval-Augmented Generation](https://arxiv.org/pdf/2603.08329)
- Mar 8 [KohakuRAG: A simple RAG framework with hierarchical document indexing](https://arxiv.org/pdf/2603.07612)
- Mar 7 [Hit-RAG: Learning to Reason with Long Contexts via Preference Alignment](https://arxiv.org/pdf/2603.07023)
- Mar 6 [LIT-RAGBench: Benchmarking Generator Capabilities of Large Language Models in Retrieval-Augmented Generation](https://arxiv.org/pdf/2603.06198)
- Mar 5 [Towards Robust Retrieval-Augmented Generation Based on Knowledge Graph: A Comparative Analysis](https://arxiv.org/pdf/2603.05698)
- Mar 5 [MedCoRAG: Interpretable Hepatology Diagnosis via Hybrid Evidence Retrieval and Multispecialty Consensus](https://arxiv.org/pdf/2603.05129)
- Mar 5 [S-Path-RAG: Semantic-Aware Shortest-Path Retrieval Augmented Generation for Multi-Hop Knowledge Graph Question Answering](https://arxiv.org/pdf/2603.23512)
- Mar 3 [RAG-X: Systematic Diagnosis of Retrieval-Augmented Generation for Medical Question Answering](https://arxiv.org/pdf/2603.03541)
- Mar 2 [URAG: A Benchmark for Uncertainty Quantification in Retrieval-Augmented Large Language Models
](https://arxiv.org/pdf/2603.19281)
- Mar 2 [GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation](https://arxiv.org/pdf/2603.01783)
- Mar 1 [Tiny-Critic RAG: Empowering Agentic Fallback with Parameter-Efficient Small Language Models](https://arxiv.org/pdf/2603.00846)
### 🔥2026 February
- Feb 28 [From Flat to Structural: Enhancing Automated Short Answer Grading with GraphRAG](https://arxiv.org/pdf/2603.19276)
- Feb 26 [TCM-DiffRAG: Personalized Syndrome Differentiation Reasoning Method for Traditional Chinese Medicine based on Knowledge Graph and Chain of Thought](https://arxiv.org/pdf/2602.22828)
- Feb 26 [Search-P1: Path-Centric Reward Shaping for Stable and Efficient Agentic RAG Training](https://arxiv.org/pdf/2602.22576)
- Feb 25 [Revisiting RAG Retrievers: An Information Theoretic Benchmark](https://arxiv.org/pdf/2602.21553)
- Feb 24 [HELP: HyperNode Expansion and Logical Path-Guided Evidence Localization for Accurate and Efficient GraphRAG](https://arxiv.org/pdf/2602.20926)
- Feb 24 [RMIT-ADM+S at the MMU-RAG NeurIPS 2025 Competition](https://arxiv.org/pdf/2602.20735)
- Feb 24 [DynaRAG: Bridging Static and Dynamic Knowledge in Retrieval-Augmented Generation](https://arxiv.org/pdf/2603.18012)
- Feb 23 [How Retrieved Context Shapes Internal Representations in RAG](https://arxiv.org/pdf/2602.20091)
- Feb 23 [Controllable Evidence Selection in Retrieval-Augmented Question Answering via Deterministic Utility Gating](https://arxiv.org/pdf/2603.18011)
- Feb 22 [AgenticRAGTracer: A Hop-Aware Benchmark for Diagnosing Multi-Step Retrieval Reasoning in Agentic RAG](https://arxiv.org/pdf/2602.19127)
- Feb 21 [Rethinking Retrieval-Augmented Generation as a Cooperative Decision-Making Problem](https://arxiv.org/pdf/2602.18734)
- Feb 20 [GraphSkill: Documentation-Guided Hierarchical Retrieval-Augmented Coding for Complex Graph Reasoning](https://arxiv.org/pdf/2603.06620)
- Feb 19 [NTLRAG: Narrative Topic Labels derived with Retrieval Augmented Generation](https://arxiv.org/pdf/2602.17216)
- Feb 19 [NotebookRAG: Retrieving Multiple Notebooks to Augment the Generation of EDA Notebooks for Crowd-Wisdom](https://arxiv.org/pdf/2602.17215)
- Feb 17 [Concept-Enhanced Multimodal RAG: Towards Interpretable and Accurate Radiology Report Generation](https://arxiv.org/pdf/2602.15650)
- Feb 16 [AIC CTU@AVerImaTeC: dual-retriever RAG for image-text fact checking](https://arxiv.org/pdf/2602.15190)
- Feb 16 [HyperRAG: Reasoning N-ary Facts over Hypergraphs for Retrieval Augmented Generation](https://arxiv.org/pdf/2602.14470)
- Feb 16 [Differentially Private Retrieval-Augmented Generation](https://arxiv.org/pdf/2602.14374)
- Feb 14 [Evaluating Prompt Engineering Techniques for RAG in Small Language Models: A Multi-Hop QA Approach](https://arxiv.org/pdf/2602.13890)
- Feb 13 [LIR^3AG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation](https://arxiv.org/abs/2512.18329)
- Feb 11 [MultiCube-RAG for Multi-hop Question Answering](https://arxiv.org/pdf/2602.15898)
- Feb 11 [AudioRAG: A Challenging Benchmark for Audio Reasoning and Information Retrieval](https://arxiv.org/pdf/2602.10656)
- Feb 10 [MLDocRAG: Multimodal Long-Context Document Retrieval Augmented Generation](https://arxiv.org/pdf/2602.10271)
- Feb 10 [Comprehensive Comparison of RAG Methods Across Multi-Domain Conversational QA](https://arxiv.org/pdf/2602.09552)
- Feb 10 [Evaluating Social Bias in RAG Systems: When External Context Helps and Reasoning Hurts](https://arxiv.org/pdf/2602.09442)
- Feb 9 [DA-RAG: Dynamic Attributed Community Search for Retrieval-Augmented Generation](https://arxiv.org/pdf/2602.08545)
- Feb 9 [SCOUT-RAG: Scalable and Cost-Efficient Unifying Traversal for Agentic Graph-RAG over Distributed Domains](https://arxiv.org/pdf/2602.08400)
- Feb 8 [HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation](https://arxiv.org/pdf/2602.07739)
- Feb 7 [IGMiRAG: Intuition-Guided Retrieval-Augmented Generation with Adaptive Mining of In-Depth Memor](https://arxiv.org/pdf/2602.07525)
- Feb 7 [Progressive Searching for Retrieval in RAG](https://arxiv.org/pdf/2602.07297)
- Feb 7 [Benchmarking Legal RAG: The Promise and Limits of AI Statutory Surveys](https://arxiv.org/pdf/2603.03300)
- Feb 6 [SE-Search: Self-Evolving Search Agent via Memory and Dense Reward](https://arxiv.org/pdf/2603.03293)
- Feb 5 [CompactRAG: Reducing LLM Calls and Token Overhead in Multi-Hop Question Answering](https://arxiv.org/pdf/2602.05728)
- Feb 5 [Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Exploration](https://arxiv.org/pdf/2602.05708)
- Feb 5 [When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering](https://arxiv.org/pdf/2601.19827)
- Feb 4[HugRAG: Hierarchical Causal Knowledge Graph Design for RAG](https://arxiv.org/pdf/2602.05143)
- Feb 4 [Pruning Minimal Reasoning Graphs for Efficient Retrieval-Augmented Generation](https://arxiv.org/pdf/2602.04926)
- Feb 4 [Atomic Information Flow: A Network Flow Model for Tool Attributions in RAG Systems](https://arxiv.org/pdf/2602.04912)
- Feb 3 [LUMINA: Detecting Hallucinations in RAG System with Context-Knowledge Signals](https://arxiv.org/pdf/2509.21875)
- Feb 3 [Rethinking the Reranker: Boundary-Aware Evidence Selection for Robust Retrieval-Augmented Generation](https://arxiv.org/pdf/2602.03689)
- Feb 3 [Reinforcement Fine-Tuning for History-Aware Dense Retriever in RAG](https://arxiv.org/pdf/2602.03645)
- Feb 3 [Use Graph When It Needs: Efficiently and Adaptively Integrating Retrieval-Augmented Generation with Graphs](https://arxiv.org/pdf/2602.03578)
- Feb 3 [A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces](https://arxiv.org/pdf/2602.03442)
- Feb 3 [Pursuing Best Industrial Practices for Retrieval-Augmented Generation in the Medical Domain](https://arxiv.org/pdf/2602.03368)
- Feb 2 [Breaking the Static Graph: Context-Aware Traversal for Robust Retrieval-Augmented Generation](https://arxiv.org/pdf/2602.01965)
- Feb 2 [CTRL-RAG: Contrastive Likelihood Reward Based Reinforcement Learning for Context-Faithful RAG Models](https://arxiv.org/pdf/2603.04406)
- Feb 2 [P-RAG: Prompt-Enhanced Parametric RAG with LoRA and Selective CoT for Biomedical and Multi-Hop QA](https://arxiv.org/pdf/2602.15874)
### 🔥2026 January
- Jan 30 [Bounding Hallucinations: Information-Theoretic Guarantees for RAG Systems via Merlin-Arthur Protocols](https://arxiv.org/pdf/2512.11614)
- Jan 30 [DIVERGE: Diversity-Enhanced RAG for Open-Ended Information Seeking](https://arxiv.org/pdf/2602.00238)
- Jan 30 [RAGRouter-Bench: A Dataset and Benchmark for Adaptive RAG Routing](https://arxiv.org/pdf/2602.00296)
- Jan 29 [ProRAG: Process-Supervised Reinforcement Learning for Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.21912)
- Jan 29 [EHR-RAG: Bridging Long-Horizon Structured Electronic Health Records and Large Language Models via Enhanced Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.21340)
- Jan 27 [LURE-RAG: Lightweight Utility-driven Reranking for Efficient RAG](https://arxiv.org/pdf/2601.19535)
- Jan 27 [RPO-RAG: Aligning Small LLMs with Relation-aware Preference Optimization for Knowledge Graph Question Answering](https://arxiv.org/pdf/2601.19225)
- Jan 24 [Less is More for RAG: Information Gain Pruning for Generator-Aligned Reranking and Evidence Selection](https://arxiv.org/pdf/2601.17532)
- Jan 23 [DeepEra: A Deep Evidence Reranking Agent for Scientific Retrieval-Augmented Generated Question Answering](https://arxiv.org/pdf/2601.16478)
- Jan 23 [DF-RAG: Query-Aware Diversity for Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.17212)
- Jan 22 [SPARC-RAG: Adaptive Sequential-Parallel Scaling with Context Management for Retrieval-Augmented Generation](https://arxiv.org/pdf/2602.00083)
- Jan 21 [ManuRAG: Multi-modal Retrieval Augmented Generation for Manufacturing Question Answering (Early Version)](https://arxiv.org/pdf/2601.15434)
- Jan 21 [MiRAGE: A Multiagent Framework for Generating Multimodal Multihop Question-Answer Dataset for RAG Evaluation](https://arxiv.org/pdf/2601.15487)
- Jan 20 [Predicting Retrieval Utility and Answer Quality in Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.14546)
- Jan 19 [RAGExplorer: A Visual Analytics System for the Comparative Diagnosis of RAG Systems](https://arxiv.org/pdf/2601.12991)
- Jan 19 [Augmenting Question Answering with A Hybrid RAG Approach](https://arxiv.org/pdf/2601.12658)
- Jan 16 [NAACL: Noise-AwAre Verbal Confidence Calibration for LLMs in RAG Systems](https://arxiv.org/pdf/2601.11004)
- Jan 16 [PruneRAG: Confidence-Guided Query Decomposition Trees for Efficient Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.11024)
- Jan 16 [Reasoning in Trees: Improving Retrieval-Augmented Generation for Multi-Hop Question Answering](https://arxiv.org/pdf/2601.11255)
- Jan 16 [Unlocking the Potentials of Retrieval-Augmented Generation for Diffusion Language Models](https://arxiv.org/pdf/2601.11342)
- Jan 16 [Deep GraphRAG: A Balanced Approach to Hierarchical Retrieval and Adaptive Integration](https://arxiv.org/pdf/2601.11144)
- Jan 16 [Predict the Retrieval! Test time adaptation for Retrieval Augmented Generation](https://arxiv.org/pdf/2601.11443)
- Jan 15 [RoutIR: Fast Serving of Retrieval Pipelines for Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.10644)
- Jan 13 [RAGShaper: Eliciting Sophisticated Agentic RAG Skills via Automated Data Synthesis](https://arxiv.org/pdf/2601.08699)
- Jan 12 [Relink: Constructing Query-Driven Evidence Graph On-the-Fly for GraphRAG](https://arxiv.org/pdf/2601.07192)
- Jan 12 [BayesRAG: Probabilistic Mutual Evidence Corroboration for Multimodal Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.07329)
- Jan 12 [FROAV: A Framework for RAG Observation and Agent Verification - Lowering the Barrier to LLM Agent Research](https://arxiv.org/pdf/2601.07504)
- Jan 12 [Is Agentic RAG worth it? An experimental comparison of RAG approaches](https://arxiv.org/pdf/2601.07711)
- Jan 11 [TreePS-RAG: Tree-based Process Supervision for Reinforcement Learning in Agentic RAG](https://arxiv.org/pdf/2601.06922)
- Jan 11 [Seeing through the Conflict: Transparent Knowledge Conflict Handling in Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.06842)
- Jan 11 [Fine-Tuning vs. RAG for Multi-Hop Question Answering with Novel Knowledge](https://arxiv.org/pdf/2601.07054)
- Jan 10 [Attribution Techniques for Mitigating Hallucinated Information in RAG Systems: A Survey](https://arxiv.org/pdf/2601.19927)
- Jan 10 [MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.06519)
- Jan 10 [L-RAG: Balancing Context and Retrieval with Entropy-Based Lazy Loading](https://arxiv.org/pdf/2601.06551)
- Jan 8 [Self-MedRAG: a Self-Reflective Hybrid Retrieval-Augmented Generation Framework for Reliable Medical Question Answering](https://arxiv.org/pdf/2601.04531)
- Jan 8 [Orion-RAG: Path-Aligned Hybrid Retrieval for Graphless Data](https://arxiv.org/pdf/2601.04764)
- Jan 8 [OptiSet: Unified Optimizing Set Selection and Ranking for Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.05027)
- Jan 8 [ArcAligner: Adaptive Recursive Aligner for Compressed Context Embeddings in RAG](https://arxiv.org/pdf/2601.05038)
- Jan 6 [Enhancing Multilingual RAG Systems with Debiased Language Preference-Guided Query Fusion](https://arxiv.org/pdf/2601.02956)
- Jan 6 [Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.02993)
- Jan 6 [Detecting Hallucinations in Retrieval-Augmented Generation via Semantic-level Internal Reasoning Graph](https://arxiv.org/pdf/2601.03052)
- Jan 6 [Tackling the Inherent Difficulty of Noise Filtering in RAG](https://arxiv.org/pdf/2601.01896)
- Jan 7 [Disco-RAG: Discourse-Aware Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.04377)
- Jan 5 [Clinical Knowledge Graph Construction and Evaluation with Multi-LLMs via Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.01844)
- Jan 4 [A Dynamic Retrieval-Augmented Generation System with Selective Memory and Remembrance](https://arxiv.org/pdf/2601.02428)
- Jan 2 [Improving Multi-step RAG with Hypergraph-based Memory for Long-Context Complex Relational Modeling](https://arxiv.org/pdf/2512.23959)
- Jan 2 [RAG-BioQA: A Retrieval-Augmented Generation Framework for Long-Form Biomedical Question Answering](https://arxiv.org/pdf/2510.01612)
### 🔥2025 December
- Dec 31 [Enhancing Retrieval-Augmented Generation with Topic-Enriched Embeddings: A Hybrid Approach Integrating Traditional NLP Techniques](https://arxiv.org/pdf/2601.00891)
- Dec 29 [Retrieval Augmented Question Answering: When Should LLMs Admit Ignorance?](https://arxiv.org/pdf/2512.23836)
- Dec 27 [DICE: Discrete Interpretable Comparative Evaluation with Probabilistic Scoring for Retrieval-Augmented Generation](https://arxiv.org/pdf/2512.22629)
- Dec 27 [HiFi-RAG: Hierarchical Content Filtering and Two-Pass Generation for Open-Domain RAG](https://arxiv.org/pdf/2512.22442)
- Dec 25 [FVA-RAG: Falsification-Verification Alignment for Mitigating Sycophantic Hallucinations](https://arxiv.org/pdf/2512.07015)
- Dec 22 [QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation](https://arxiv.org/pdf/2512.19134)
- Dec 20 [Bidirectional RAG: Safe Self-Improving Retrieval-Augmented Generation Through Multi-Stage Validation](https://arxiv.org/pdf/2512.22199)
- Dec 19 [MMRAG-RFT: Two-stage Reinforcement Fine-tuning for Explainable Multi-modal Retrieval-augmented Generation](https://arxiv.org/pdf/2512.17194)
- Dec 17 [The Semantic Illusion: Certified Limits of Embedding-Based Hallucination Detection in RAG Systems](https://arxiv.org/pdf/2512.15068)
- Dec 16 [DrugRAG: Enhancing Pharmacy LLM Performance Through A Novel Retrieval-Augmented Generation Pipeline](https://arxiv.org/pdf/2512.14896)
- Dec 16 [Dynamic Context Selection for Retrieval-Augmented Generation: Mitigating Distractors and Positional Bias](https://arxiv.org/pdf/2512.14313)
- Dec 16 [Cog-RAG: Cognitive-Inspired Dual-Hypergraph with Theme Alignment Retrieval-Augmented Generation](https://arxiv.org/pdf/2511.13201)
- Dec 15 [Semantic Grounding Index: Geometric Bounds on Context Engagement in RAG Systems](https://arxiv.org/pdf/2512.13771)
- Dec 12 [LOOPRAG: Enhancing Loop Transformation Optimization with Retrieval-Augmented Large Language Models](https://arxiv.org/pdf/2512.15766)
- Dec 11 [Cooperative Retrieval-Augmented Generation for Question Answering: Mutual Information Exchange and Ranking by Contrasting Layers](https://arxiv.org/pdf/2512.10422)
- Dec 10 [MedBioRAG: Semantic Search and Retrieval-Augmented Generation with Large Language Models for Medical and Biological QA](https://arxiv.org/pdf/2512.10996)
- Dec 10 [RouteRAG: Efficient Retrieval-Augmented Generation from Text and Graph via Reinforcement Learning](https://arxiv.org/pdf/2512.09487)
- Dec 10 [Leveraging Language Models and RAG for Efficient Knowledge Discovery in Clinical Environments](https://arxiv.org/pdf/2601.04209)
- Dec 9 [Detecting Hallucinations in Graph Retrieval-Augmented Generation via Attention Patterns and Semantic Alignment](https://arxiv.org/pdf/2512.09148)
- Dec 9 [Toward Faithful Retrieval-Augmented Generation with Sparse Autoencoders](https://arxiv.org/pdf/2512.08892)
- Dec 5 [Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework](https://arxiv.org/pdf/2512.05863)
- Dec 3 [RAGVUE: A Diagnostic View for Explainable and Automated Evaluation of Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.04196)
- Dec 3 [BookRAG: A Hierarchical Structure-aware Index-based Approach for Retrieval-Augmented Generation on Complex Documents](https://arxiv.org/pdf/2512.03413)
### 🔥2025 November
- Nov 29 [Breaking It Down: Domain-Aware Semantic Segmentation for Retrieval Augmented Generation](https://arxiv.org/pdf/2512.00367)
- Nov 28 [Autonomous QA Agent: A Retrieval-Augmented Framework for Reliable Selenium Script Generation](https://arxiv.org/pdf/2601.06034)
- Nov 27 [Unlocking Electronic Health Records: A Hybrid Graph RAG Approach to Safe Clinical AI for Patient QA](https://arxiv.org/pdf/2602.00009)
- Nov 26 [MegaRAG: Multimodal Knowledge Graph-Based Retrieval Augmented Generation](https://arxiv.org/pdf/2512.20626)
- Nov 25 [HKRAG: Holistic Knowledge Retrieval-Augmented Generation Over Visually-Rich Documents](https://arxiv.org/pdf/2511.20227)
- Nov 24 [HyperbolicRAG: Enhancing Retrieval-Augmented Generation with Hyperbolic Representations](https://arxiv.org/pdf/2511.18808)
- Nov 22 [Agent-as-a-Graph: Knowledge Graph-Based Tool and Agent Retrieval for LLM Multi-Agent Systems](https://arxiv.org/pdf/2511.18194)
- Nov 22 [Rethinking Retrieval: From Traditional Retrieval Augmented Generation to Agentic and Non-Vector Reasoning Systems in the Financial Domain for Large Language Models](https://arxiv.org/pdf/2511.18177)
- Nov 21 [Beyond Component Strength: Synergistic Integration and Adaptive Calibration in Multi-Agent RAG Systems](https://arxiv.org/pdf/2511.21729)
- Nov 20 [Comparison of Text-Based and Image-Based Retrieval in Multimodal Retrieval Augmented Generation Large Language Model Systems](https://arxiv.org/pdf/2511.16654)
- Nov 19 [CARE-RAG - Clinical Assessment and Reasoning in RAG](https://arxiv.org/pdf/2511.15994)
- Nov 19 [ItemRAG: Item-Based Retrieval-Augmented Generation for LLM-Based Recommendation](https://arxiv.org/pdf/2511.15141)
- Nov 19 [Noise-Robust Abstractive Compression in Retrieval-Augmented Language Models](https://arxiv.org/pdf/2512.08943)
- Nov 18 [LiveRAG: A diverse Q&A dataset with varying difficulty level for RAG evaluation](https://arxiv.org/pdf/2511.14531)
- Nov 17 [TelcoAI: Advancing 3GPP Technical Specification Search through Agentic Multi-Modal Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.16984)
- Nov 16 [TAdaRAG: Task Adaptive Retrieval-Augmented Generation via On-the-Fly Knowledge Graph Construction](https://arxiv.org/pdf/2511.12520)
- Nov 15 [MME-RAG: Multi-Manager-Expert Retrieval-Augmented Generation for Fine-Grained Entity Recognition in Task-Oriented Dialogues](https://arxiv.org/pdf/2511.12213)
- Nov 13 [Modeling Uncertainty Trends for Timely Retrieval in Dynamic RAG](https://arxiv.org/pdf/2511.09980)
- Nov 13 [TruthfulRAG: Resolving Factual-level Conflicts in Retrieval-Augmented Generation with Knowledge Graphs](https://arxiv.org/pdf/2511.10375)
- Nov 13 [RAGFort: Dual-Path Defense Against Proprietary Knowledge Base Extraction in Retrieval-Augmented Generation](https://arxiv.org/pdf/2511.10128)
- Nov 12 [BarrierBench : Evaluating Large Language Models for Safety Verification in Dynamical Systems](https://arxiv.org/pdf/2511.09363)
- Nov 10 [Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training](https://arxiv.org/pdf/2511.07328)
- Nov 10 [A survey: Information search time optimization based on RAG (Retrieval Augmentation Generation) chatbot](https://arxiv.org/pdf/2601.07838)
- Nov 8 [Cross-Document Topic-Aligned Chunking for Retrieval-Augmented Generation](https://arxiv.org/pdf/2601.05265)
- Nov 8 [Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations](https://arxiv.org/pdf/2511.05901)
- Nov 7 [TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework](https://arxiv.org/pdf/2511.05385)
- Nov 6 [RAGalyst: Automated Human-Aligned Agentic Evaluation for Domain-Specific RAG](https://arxiv.org/pdf/2511.04502)
- Nov 5 [RAGBoost: Efficient Retrieval-Augmented Generation with Accuracy-Preserving Context Reuse](https://arxiv.org/pdf/2511.03475)
- Nov 1 [Zero-RAG: Towards Retrieval-Augmented Generation with Zero Redundant Knowledge](https://arxiv.org/pdf/2511.00505)
### 🔥2025 October
- Oct 29 [DIRC-RAG: Accelerating Edge RAG with Robust High-Density and High-Loading-Bandwidth Digital In-ReRAM Computation](https://arxiv.org/pdf/2510.25278)
- Oct 28 [Mitigating Hallucination in Large Language Models (LLMs): An Application-Oriented Survey on RAG, Reasoning, and Agentic Systems](https://arxiv.org/pdf/2510.24476)
- Oct 28 [META-RAG: Meta-Analysis-Inspired Evidence-Re-Ranking Method for Retrieval-Augmented Generation in Evidence-Based Medicine](https://arxiv.org/pdf/2510.24003)
- Oct 28 [PICOs-RAG: PICO-supported Query Rewriting for Retrieval-Augmented Generation in Evidence-Based Medicine](https://arxiv.org/pdf/2510.23998)
- Oct 25 [FAIR-RAG: Faithful Adaptive Iterative Refinement for Retrieval-Augmented Generation](https://arxiv.org/pdf/2510.22344)
- Oct 24 [InterpDetect: Interpretable Signals for Detecting Hallucinations in Retrieval-Augmented Generation](https://arxiv.org/pdf/2510.21538)
- Oct 24 [SUBQRAG: Sub-Question Driven Dynamic Graph RAG](https://arxiv.org/pdf/2510.07718)
- Oct 21 [Is Implicit Knowledge Enough for LLMs? A RAG Approach for Tree-based Structures](https://arxiv.org/pdf/2510.10806)
- Oct 21 [Query Decomposition for RAG: Balancing Exploration-Exploitation](https://arxiv.org/pdf/2510.18633)
- Oct 17 [RAG vs. GraphRAG: A Systematic Evaluation and Key Insights](https://arxiv.org/pdf/2502.11371)
- Oct 17 [Stop-RAG: Value-Based Retrieval Control for Iterative RAG](https://arxiv.org/pdf/2510.14337)
- Oct 16 [Multimodal RAG for Unstructured Data:Leveraging Modality-Aware Knowledge Graphs with Hybrid Retrieval](https://arxiv.org/pdf/2510.14592)
- Oct 16 [MoM: Mixtures of Scenario-Aware Document Memories for Retrieval-Augmented Generation Systems](https://arxiv.org/pdf/2510.14252)
- Oct 15 [ReMindRAG: Low-Cost LLM-Guided Knowledge Graph Traversal for Efficient RAG](https://arxiv.org/pdf/2510.13193)
- Oct 15 [RAG Meets Temporal Graphs: Time-Sensitive Modeling and Retrieval for Evolving Knowledge](https://arxiv.org/pdf/2510.13590)
- Oct 15 [SeCon-RAG: A Two-Stage Semantic Filtering and Conflict-Free Framework for Trustworthy RAG](https://arxiv.org/pdf/2510.09710)
- Oct 14 [PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation](https://arxiv.org/pdf/2510.12434)
- Oct 14 [RAG-Anything: All-in-One RAG Framework](https://arxiv.org/pdf/2510.12323)
- Oct 13 [Domain-Specific Data Generation Framework for RAG Adaptation](https://arxiv.org/pdf/2510.11217)
- Oct 12 [RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation](https://arxiv.org/pdf/2510.10448)
- Oct 12 [Multimodal Retrieval-Augmented Generation with Large Language Models for Medical VQA](https://arxiv.org/pdf/2510.13856)
- Oct 11 [LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora](https://arxiv.org/pdf/2510.10114)
- Oct 11 [RAG-IGBench: Innovative Evaluation for RAG-based Interleaved Generation in Open-domain Question Answering](https://arxiv.org/pdf/2512.05119)
- Oct 10 [Use of Retrieval-Augmented Large Language Model Agent for Long-Form COVID-19 Fact-Checking](https://arxiv.org/pdf/2512.00007)
- Oct 10 [Chain-of-Retrieval Augmented Generation](https://arxiv.org/pdf/2501.14342)
- Oct 10 [When Retrieval Succeeds and Fails: Rethinking Retrieval-Augmented Generation for LLMs](https://arxiv.org/pdf/2510.09106)
- Oct 9 [QAgent: A modular Search Agent with Interactive Query Understanding](https://arxiv.org/pdf/2510.08383)
- Oct 9 [STEPER: Step-wise Knowledge Distillation for Enhancing Reasoning Ability in Multi-Step Retrieval-Augmented Language Models](https://arxiv.org/pdf/2510.07923)
- Oct 7 [HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation](https://arxiv.org/pdf/2510.07794)
- Oct 6 [MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts](https://arxiv.org/pdf/2510.05363)
- Oct 4 [Beyond Outcome Reward: Decoupling Search and Answering Improves LLM Agents](https://arxiv.org/pdf/2510.04695)
- Oct 4 [Equipping Retrieval-Augmented Large Language Models with Document Structure Awareness](https://arxiv.org/pdf/2510.04293)
- Oct 2 [Less LLM, More Documents: Searching for Improved RAG](https://arxiv.org/pdf/2510.02657)
- Oct 2 [Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation](https://arxiv.org/pdf/2510.02388)
- Oct 2 [Training Dynamics of Parametric and In-Context Knowledge Utilization in Language Models](https://arxiv.org/pdf/2510.02370)
- Oct 2 [AccurateRAG: A Framework for Building Accurate Retrieval-Augmented Question-Answering Applications](https://arxiv.org/pdf/2510.02243)
- Oct 1 [A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation](https://arxiv.org/pdf/2510.01600)
- Oct 1 [Fine-tuning with RAG for Improving LLM Learning of New Skills](https://arxiv.org/pdf/2510.01375)
- Oct 1 [GRAD: Generative Retrieval-Aligned Demonstration Sampler for Efficient Few-Shot Reasoning](https://arxiv.org/pdf/2510.01165)
- Oct 1 [HalluGuard: Evidence-Grounded Small Reasoning Models to Mitigate Hallucinations in Retrieval-Augmented Generation](https://arxiv.org/pdf/2510.00880)
### 🍭2025 September
- Sep 30 [RAGferee: Building Contextual Reward Models for Retrieval-Augmented Generation](https://arxiv.org/pdf/2509.26011)
- Sep 27 [From Evidence to Trajectory: Abductive Reasoning Path Synthesis for Training Retrieval-Augmented Generation Agents](https://arxiv.org/pdf/2509.23071)
- Sep 26 [Beyond RAG vs. Long-Context: Learning Distraction-Aware Retrieval for Efficient Knowledge Grounding](https://arxiv.org/pdf/2509.21865)
- Sep 26 [Can Synthetic Query Rewrites Capture User Intent Better than Humans in Retrieval-Augmented Generation?](https://arxiv.org/pdf/2509.22325)
- Sep 25 [Concise and Sufficient Sub-Sentence Citations for Retrieval-Augmented Generation](https://arxiv.org/pdf/2509.20859)
- Sep 24 [RAR2: Retrieval-Augmented Medical Reasoning via Thought-Driven Retrieval](https://arxiv.org/pdf/2509.22713)
- Sep 22 [AttnComp: Attention-Guided Adaptive Context Compression for Retrieval-Augmented Generation](https://arxiv.org/pdf/2509.17486)
- Sep 21 [Influence Guided Context Selection for Effective Retrieval-Augmented Generation](https://arxiv.org/pdf/2509.21359)
- Sep 20 [SKILL-RAG: Self-Knowledge Induced Learning and Filtering for Retrieval-Augmented Generation](https://arxiv.org/pdf/2509.20377)
- Sep 19 [Relevance to Utility: Process-Supervised Rewrite for RAG](https://arxiv.org/pdf/2509.15577)
- Sep 17 [Improving Context Fidelity via Native Retrieval-Augmented Reasoning](https://arxiv.org/pdf/2509.13683)
- Sep 9 [Rethinking LLM Parametric Knowledge as Post-retrieval Confidence for Dynamic Retrieval and Reranking](https://arxiv.org/pdf/2509.06472)
- Sep 8 [HANRAG: Heuristic Accurate Noise-resistant Retrieval-Augmented Generation for Multi-hop Question Answering](https://arxiv.org/pdf/2509.09713)
- Sep 8 [Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval](https://arxiv.org/pdf/2509.06650)
- Sep 8 [HAVE: Head-Adaptive Gating and ValuE Calibration for Hallucination Mitigation in Large Language Models](https://arxiv.org/pdf/2509.06596)
- Sep 5 [Fishing for Answers: Exploring One-shot vs. Iterative Retrieval Strategies for Retrieval Augmented Generation](https://arxiv.org/pdf/2509.04820)
- Sep 5 [KERAG: Knowledge-Enhanced Retrieval-Augmented Generation for Advanced Question Answering](https://arxiv.org/pdf/2509.04716)
- Sep 4 [SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment](https://arxiv.org/pdf/2509.03934)
- Sep 4 [MobileRAG: Enhancing Mobile Agent with Retrieval-Augmented Generation](https://arxiv.org/pdf/2509.03891)
- Sep 2 [Better by Comparison: Retrieval-Augmented Contrastive Reasoning for Automatic Prompt Optimization](https://arxiv.org/pdf/2509.02093)
- Sep 1 [REFRAG: Rethinking RAG based Decoding](https://arxiv.org/pdf/2509.01092)
- Sep 1 [Towards Open-World Retrieval-Augmented Generation on Knowledge Graph: A Multi-Agent Collaboration Framework](https://arxiv.org/pdf/2509.01238)
### 🍭2025 August
- Aug 29 [Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward](https://arxiv.org/pdf/2508.12800)
- Aug 27 [Understanding and Leveraging the Expert Specialization of Context Faithfulness in Mixture-of-Experts LLMs](https://arxiv.org/pdf/2508.19594)
- Aug 27 [Can Compact Language Models Search Like Agents? Distillation-Guided Policy Optimization for Preserving Agentic RAG Capabilities](https://arxiv.org/pdf/2508.20324)
- Aug 27 [LFD: Layer Fused Decoding to Exploit External Knowledge in Retrieval-Augmented Generation](https://arxiv.org/pdf/2508.19614)
- Aug 26 [Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains](https://arxiv.org/pdf/2508.19357)
- Aug 25 [Improving End-to-End Training of Retrieval-Augmented Generation Models via Joint Stochastic Approximation](https://arxiv.org/pdf/2508.18168)
- Aug 24 [CORE: Lossless Compression for Retrieval-Augmented LLMs via Reinforcement Learning](https://arxiv.org/pdf/2508.19282)
- Aug 24 [SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer](https://arxiv.org/pdf/2508.17556)
- Aug 24 [SSFO: Self-Supervised Faithfulness Optimization for Retrieval-Augmented Generation](https://arxiv.org/pdf/2508.17225)
- Aug 21 [Conflict-Aware Soft Prompting for Retrieval-Augmented Generation](https://arxiv.org/pdf/2508.15253)
- Aug 21 [Select to Know: An Internal-External Knowledge Self-SelectionFramework for Domain-Specific Question Answering](https://arxiv.org/pdf/2508.15213)
- Aug 18 [LeanRAG: Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval](https://arxiv.org/pdf/2508.10391)
- Aug 15 [Cross-Granularity Hypergraph Retrieval-Augmented Generation for Multi-hop Question Answering](https://arxiv.org/pdf/2508.11247)
- Aug 14 [SSRL: Self-Search Reinforcement Learning](https://arxiv.org/pdf/2508.10874)
- Aug 14 [ComoRAG: A Cognitive-Inspired Memory-Organized RAG for Stateful Long Narrative Reasoning](https://arxiv.org/pdf/2508.10419)
- Aug 13 [Towards Self-cognitive Exploration: Metacognitive Knowledge Graph Retrieval Augmented Generation](https://arxiv.org/pdf/2508.09460v1)
- Aug 13 [Transforming Questions and Documents for Semantically Aligned Retrieval-Augmented Generation](https://arxiv.org/pdf/2508.09755)
- Aug 12 [READER: Retrieval-Assisted Drafter for Efficient LLM Inference](https://arxiv.org/abs/2508.09072)
- Aug 12 [REX-RAG: Reasoning Exploration with Policy Correction in Retrieval-Augmented Generation](https://arxiv.org/pdf/2508.08149)
- Aug 11 [LAG: Logic-Augmented Generation from a Cartesian Perspective](https://arxiv.org/pdf/2508.05509)
- Aug 11 [Careful Queries, Credible Results: Teaching RAG Models Advanced Web Search Tools with Reinforcement Learning](https://arxiv.org/pdf/2508.07956)
- Aug 10 [PrLM: Learning Explicit Reasoning for Personalized RAG via Contrastive Reward Optimization](https://arxiv.org/pdf/2508.07342)
- Aug 8 [Guided Decoding and Its Critical Role in Retrieval-Augmented Generation](https://arxiv.org/pdf/2509.06631)
- Aug 8 [UR2: Unify RAG and Reasoning through Reinforcement Learning](https://arxiv.org/pdf/2508.06165)
- Aug 8 [Spectrum Projection Score: Aligning Retrieved Summaries with Reader Models in Retrieval-Augmented Generation](https://arxiv.org/pdf/2508.05909v1)
- Aug 7 [BEE-RAG: Balanced Entropy Engineering for Retrieval-Augmented Generation](https://www.arxiv.org/pdf/2508.05100)
- Aug 6 [PAIRS: Parametric–Verified Adaptive Information Retrieval and Selection for Efficient RAG](https://arxiv.org/pdf/2508.04057)
- Aug 5 [Collaborative Chain-of-Agents for Parametric-Retrieved Knowledge Synergy](https://arxiv.org/pdf/2508.01696)
- Aug 1 [MAO-ARAG: Multi-Agent Orchestration for Adaptive Retrieval-Augmented Generation](https://arxiv.org/pdf/2508.01005)
### 🍭2025 July
- Jul 29 [FrugalRAG: Learning to retrieve and reason for multi-hop QA](https://arxiv.org/pdf/2507.07634)
- Jul 25 [Injecting External Knowledge into the Reasoning Process Enhances Retrieval-Augmented Generation](https://arxiv.org/pdf/2507.19333)
- Jul 25 [Distilling a Small Utility-Based Passage Selector to Enhance Retrieval-Augmented Generation](https://arxiv.org/pdf/2507.19102v1)
- Jul 25 [Query-Aware Graph Neural Networks for Enhanced Retrieval-Augmented Generation](https://www.arxiv.org/pdf/2508.05647)
- Jul 23 [HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge](https://arxiv.org/pdf/2503.10150)
- Jul 15 [RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism](https://arxiv.org/pdf/2507.02962)
### 🍭2025 June
- Jun 20 [PreQRAG -- Classify and Rewrite for Enhanced RAG](https://arxiv.org/pdf/2506.17493)
- Jun 15 [Intra-Trajectory Consistency for Reward Modeling](https://www.arxiv.org/pdf/2506.09096)
- Jun 5 [Knowledgeable-r1: Policy Optimization for Knowledge Exploration in Retrieval-Augmented Generation](https://arxiv.org/pdf/2506.05154v1)
- Jun 4 [R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement Learning](https://arxiv.org/pdf/2506.04185v1)
- Jun 2 [ImpRAG: Retrieval-Augmented Generation with Implicit Queries](https://arxiv.org/pdf/2506.02279)
### 🥇ACL 2025
$main$
Methods & Pipeline & Framework
- [GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis](https://arxiv.org/pdf/2505.18710) [\[Code\]](https://github.com/liunian-Jay/GainRAG)
- [FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation](https://arxiv.org/pdf/2506.08938) [\[Code\]](https://github.com/XMUDeepLIT/Faithful-RAG)
- [RPO: Retrieval Preference Optimization for Robust Retrieval-Augmented Generation](https://arxiv.org/pdf/2501.13726v1)
- [RankCoT: Refining Knowledge for Retrieval-Augmented Generation through Ranking Chain-of-Thoughts](https://arxiv.org/pdf/2502.17888)
- [Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning](https://arxiv.org/pdf/2410.10360)
- [RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Models](https://arxiv.org/pdf/2412.02830)
- [Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG](https://arxiv.org/pdf/2505.20871)
- [MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation](https://arxiv.org/pdf/2501.00332)
- [DualRAG: A Dual-Process Approach to Integrate Reasoning and Retrieval for Multi-Hop Question Answering](https://arxiv.org/pdf/2504.18243)
- [DioR: Adaptive Cognitive Detection and Contextual Retrieval Optimization for Dynamic Retrieval-Augmented Generation](https://arxiv.org/pdf/2504.10198)
- [Hierarchical Document Refinement for Long-context Retrieval-augmented Generation](https://arxiv.org/pdf/2505.10413)
- [KiRAG: Knowledge-Driven Iterative Retriever for Enhancing Retrieval-Augmented Generation](https://arxiv.org/pdf/2502.18397)
- [Enhancing Retrieval-Augmented Generation via Evidence Tree Search](https://arxiv.org/pdf/2503.20757)
- [Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering](https://arxiv.org/pdf/2502.14245)
- [SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation](https://arxiv.org/pdf/2406.19215)
- [TC–RAG: Turing–Complete RAG’s Case study on Medical LLM Systems](https://arxiv.org/pdf/2408.09199)
- [Removal of Hallucination on Hallucination: Debate-Augmented RAG](https://arxiv.org/pdf/2505.18581)
- [Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks](https://arxiv.org/pdf/2410.01428)
- [Optimizing Question Semantic Space for Dynamic Retrieval-Augmented Multi-hop Question Answering](https://arxiv.org/pdf/2506.00491)
- [UniRAG: Unified Query Understanding Method for Retrieval Augmented Generation](https://openreview.net/attachment?id=h68SaHDtal&name=pdf)
- [DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation](https://arxiv.org/pdf/2506.01954)
- [Lexical Diversity-aware Relevance Assessment for Retrieval-Augmented Generation](https://openreview.net/pdf?id=omv3VfVIQt)
- [RAG-Critic: Leveraging Automated Critic-Guided Agentic Workflow for Retrieval Augmented Generation](https://aclanthology.org/2025.acl-long.179.pdf)
- [Sparse Latents Steer Retrieval-Augmented Generation](https://aclanthology.org/2025.acl-long.228.pdf)
- [GRAT: Guiding Retrieval-Augmented Reasoning through Process Rewards Tree Search](https://aclanthology.org/2025.acl-long.1352.pdf)
- [LLMs Trust Humans More, That’s a Problem! Unveiling and Mitigating the Authority Bias in Retrieval-Augmented Generation](https://aclanthology.org/2025.acl-long.1400.pdf)
- [Shifting from Ranking to Set Selection for Retrieval Augmented Generation](https://aclanthology.org/2025.acl-long.861.pdf)
- [Dialogue-RAG: Enhancing Retrieval for LLMs via Node-Linking Utterance Rewriting](https://aclanthology.org/2025.acl-long.1191.pdf)
- [SGIC: A Self-Guided Iterative Calibration Framework for RAG](https://aclanthology.org/2025.acl-long.1376.pdf)
Benchmark & Evaluation & Analysis
- [SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model](https://arxiv.org/pdf/2501.18636)
- [HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases](https://arxiv.org/pdf/2412.16311)
- [RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework](https://arxiv.org/pdf/2408.01262)
- [Unanswerability Evaluation for Retrieval Augmented Generation](https://arxiv.org/pdf/2412.12300)
- [MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation](https://arxiv.org/pdf/2502.17163)
- [Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models](https://arxiv.org/pdf/2410.07176)
- [The Distracting Effect: Understanding Irrelevant Passages in RAG](https://arxiv.org/pdf/2505.06914)
- [Pandora’s Box or Aladdin’s Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models](https://arxiv.org/pdf/2408.13533)
- [A Reality Check on Context Utilisation for Retrieval-Augmented Generation](https://arxiv.org/pdf/2412.17031)
- [MT-RAIG: Novel Benchmark and Evaluation Framework for Retrieval-Augmented Insight Generation over Multiple Tables](https://arxiv.org/pdf/2502.11735)
- [On the Robustness of RAG Systems in Educational Question Answering under Knowledge Discrepancies](https://aclanthology.org/2025.acl-short.16.pdf)
Chunk & Database
- [MoC: Mixtures of Text Chunking Learners for Retrieval-Augmented Generation System](https://arxiv.org/pdf/2503.09600)
- [HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation](https://arxiv.org/pdf/2503.04800)
- [Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs](https://arxiv.org/pdf/2410.11001)
Application
- [Towards Omni-RAG: Comprehensive Retrieval-Augmented Generation for Large Language Models in Medical Applications](https://arxiv.org/pdf/2501.02460)
- [Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation](https://arxiv.org/pdf/2501.02226)
- [Medical Graph RAG: Evidence-based Medical Large Language Model via Graph Retrieval-Augmented Generation](https://arxiv.org/pdf/2408.04187)
- [VISA: Retrieval Augmented Generation with Visual Source Attribution](https://arxiv.org/pdf/2412.14457)
- [The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit](https://arxiv.org/pdf/2501.02173)
- [HyKGE: A Hypothesis Knowledge Graph Enhanced RAG Framework for Accurate and Reliable Medical LLMs Responses](https://arxiv.org/pdf/2312.15883)
- [NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question Answering](https://arxiv.org/abs/2505.19754)
- [CoRe-MMRAG: Cross-Source Knowledge Reconciliation for Multimodal RAG](https://arxiv.org/pdf/2506.02544)
- [Retrieval-Augmented Fine-Tuning With Preference Optimization For Visual Program Generation](https://arxiv.org/pdf/2502.16529)
$fingdings$
- [Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation](https://arxiv.org/pdf/2412.08519)
- [SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation](https://arxiv.org/pdf/2412.15272)
- [EXIT: Context-Aware Extractive Compression for Enhancing Retrieval-Augmented Generation](https://arxiv.org/pdf/2412.12559)
- [Judge as A Judge: Improving the Evaluation of Retrieval-Augmented Generation through the Judge-Consistency of Large Language Models](https://arxiv.org/pdf/2502.18817)
- [RASD: Retrieval-Augmented Speculative Decoding](https://arxiv.org/pdf/2503.03434)
- [FRAG: A Flexible Modular Framework for Retrieval-Augmented Generation based on Knowledge Graphs](https://arxiv.org/pdf/2501.09957)
- [Towards Adaptive Memory-Based Optimization for Enhanced Retrieval-Augmented Generation](https://arxiv.org/pdf/2504.05312)
- [Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning](https://arxiv.org/pdf/2502.14361)
- [Fine-grained Knowledge Enhancement for Retrieval-Augmented Generation](https://arxiv.org/pdf/2502.20964)
- [GeAR: Graph-enhanced Agent for Retrieval-augmented Generation](https://arxiv.org/pdf/2412.18431)
- [CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control](https://arxiv.org/pdf/2405.18727)
- [RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization](https://arxiv.org/pdf/2502.10993)
- [The Silent Saboteur: Imperceptible Adversarial Attacks against Black-Box Retrieval-Augmented Generation Systems](https://www.arxiv.org/pdf/2505.18583)
- [PISCO: Pretty Simple Compression for Retrieval-Augmented Generation](https://arxiv.org/pdf/2501.16075)
- [RAPID: Efficient Retrieval-Augmented Long Text Generation with Writing Planning and Information Discovery](https://arxiv.org/pdf/2503.00751)
- [Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation](https://arxiv.org/pdf/2502.08826)
- [CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation](https://arxiv.org/pdf/2503.19878)
- [Mitigating Bias in RAG: Controlling the Embedder](https://arxiv.org/pdf/2502.17390)
- [HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval Augmented Generation](https://arxiv.org/pdf/2502.12442)
- [SynapticRAG: Enhancing Temporal Memory Retrieval in Large Language Models through Synaptic Mechanisms](https://arxiv.org/pdf/2410.13553v2)
- [HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation](https://arxiv.org/pdf/2505.16133v3)
- [RAG-RewardBench: Benchmarking Reward Models in Retrieval Augmented Generation for Preference Alignment](https://arxiv.org/pdf/2412.13746)
- [LLMs are Biased Evaluators But Not Biased for Retrieval Augmented Generation](https://arxiv.org/pdf/2410.20833)
- [Accelerating Adaptive Retrieval Augmented Generation via Instruction-Driven Representation Reduction of Retrieval Overlaps](https://arxiv.org/pdf/2505.12731)
- [Evaluation of Attribution Bias in Generator-Informed Retrieval-Augmented Large Language Models](https://arxiv.org/pdf/2410.12380)
- [Axiomatic Analysis of Uncertainty Estimation For Retrieval Augmented Generation](https://openreview.net/pdf?id=kaPcDVLZEm)
- [ECoRAG: Evidentiality-guided Compression for Long Context RAG](https://arxiv.org/pdf/2506.05167)
- [GNN-RAG: Graph Neural Retrieval for Efficient Large Language Model Reasoning on Knowledge Graphs](https://arxiv.org/pdf/2405.20139)
- [LTRAG: Enhancing autoformalization and self-refinement for logical reasoning with Thought-Guided RAG](https://openreview.net/pdf?id=6WQZCc9qQ1)
- [Toward Structured Knowledge Reasoning: Contrastive Retrieval-Augmented Generation on Experience](https://arxiv.org/pdf/2506.00842)
- [Document Segmentation Matters for Retrieval-Augmented Generation](https://openreview.net/pdf?id=yToEot3imW)
- [Exploring Knowledge Filtering for Retrieval-Augmented Discriminative Tasks](https://aclanthology.org/2025.findings-acl.86.pdf)
- [TreeRAG: Unleashing the Power of Hierarchical Storage for Enhanced Knowledge Retrieval in Long Documents](https://aclanthology.org/2025.findings-acl.20.pdf)
- [EC-RAFT: Automated Generation of Clinical Trial Eligibility Criteria through Retrieval-Augmented Fine-Tuning](https://aclanthology.org/2025.findings-acl.491.pdf)
- [RASPberry: Retrieval-Augmented Monte Carlo Tree Self-Play with Reasoning Consistency for Multi-Hop Question Answering](https://aclanthology.org/2025.findings-acl.587.pdf)
- [Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection](https://aclanthology.org/2025.findings-acl.1263.pdf)
- [All That Glitters is Not Gold: Improving Robust Retrieval-Augmented Language Models with Fact-Centric Preference Alignment](https://aclanthology.org/2025.findings-acl.588.pdf)
### 🍭2025 May
- May 30 [ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering](https://arxiv.org/pdf/2506.00232)
- May 30 [Pangu DeepDiver: Adaptive Search Intensity Scaling via Open-Web Reinforcement Learning](https://arxiv.org/pdf/2505.24332)
- May 30 [ClueAnchor: Clue-Anchored Knowledge Reasoning Exploration and Optimization for Retrieval-Augmented Generation](https://arxiv.org/pdf/2505.24388)
- May 26 [R3-RAG: Learning Step-by-Step Reasoning and Retrieval for LLMs via Reinforcement Learning](https://arxiv.org/pdf/2505.23794)
- May 26 [Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers](https://arxiv.org/pdf/2505.20128)
- May 24 [GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis](https://arxiv.org/pdf/2505.18710) [\[Code\]](https://github.com/liunian-Jay/GainRAG)
- May 23 [Curriculum Guided Reinforcement Learning for Efficient Multi Hop Retrieval Augmented Generation](http://export.arxiv.org/pdf/2505.17391)
- May 22 [C-3PO: Compact Plug-and-Play Proxy Optimization to Achieve Human-like Retrieval-Augmented Generation](https://arxiv.org/pdf/2502.06205)
- May 22 [R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMsvia Reinforcement Learning](https://arxiv.org/pdf/2505.17005)
- May 22 [SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory Synthesis](https://arxiv.org/pdf/2505.16834)
- May 22 [O2-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering](https://arxiv.org/pdf/2505.16582)
- May 22 [Attributing Response to Context: A Jensen–Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation](https://arxiv.org/pdf/2505.16415)
- May 21 [Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains](https://arxiv.org/pdf/2505.16014)
- May 20 [s3: You Don’t Need That Much Data to Train a Search Agent via RL](https://arxiv.org/pdf/2505.14146)
- May 19 [Finetune-RAG: Fine-Tuning Language Models to Resist Hallucination in Retrieval-Augmented Generation](https://arxiv.org/pdf/2505.10792)
- May 15 [CL-RAG: Bridging the Gap in Retrieval-Augmented Generation with Curriculum Learning](https://arxiv.org/pdf/2505.10493)
- May 8 [Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning](https://arxiv.org/pdf/2503.06034)
- May 6 [An Analysis of Hyper-Parameter Optimization Methods for Retrieval Augmented Generation](https://arxiv.org/pdf/2505.03452)
- May 5 [Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models](https://arxiv.org/pdf/2505.03075)
- May 2 [Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation](https://arxiv.org/pdf/2505.01073)
### 🍭2025 April
- Apri 25 [DualRAG: A Dual-Process Approach to Integrate Reasoning and Retrieval for Multi-Hop Question Answering](https://arxiv.org/pdf/2504.18243)
- Apri 23 [Credible plan-driven RAG method for Multi-hop Question Answering](https://arxiv.org/pdf/2504.16787)
- Apri 22 [Exploiting Contextual Knowledge in LLMs through V-usable Information based Layer Enhancement](https://arxiv.org/pdf/2504.15630)
- Apri 21 [AlignRAG: An Adaptable Framework for Resolving Misalignments in Retrieval-Aware Reasoning of RAG](https://arxiv.org/pdf/2504.14858)
- Apri 17 [DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments](https://arxiv.org/pdf/2504.03160)
- Apri 17 [CDF-RAG: Causal Dynamic Feedback for Adaptive Retrieval-Augmented Generation](https://arxiv.org/pdf/2504.12560)
- Apri 17 [Accommodate Knowledge Conflicts in Retrieval-augmented LLMs: Towards Reliable Response Generation in the Wild](https://arxiv.org/pdf/2504.12982)
- Apri 17 [ACoRN: Noise-Robust Abstractive Compression in Retrieval-Augmented Language Models](https://arxiv.org/pdf/2504.12673)
- Apri 15 [Preference-based Learning with Retrieval Augmented Generation for Conversational Question Answering](https://arxiv.org/pdf/2503.22303)
- Apri 10 [Plan-and-Refine: Diverse and Comprehensive Retrieval-Augmented Generation](https://arxiv.org/pdf/2504.07794)
- Apri 8 [Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning](https://arxiv.org/pdf/2503.09516)
- Apri 7 [Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaboration](https://arxiv.org/pdf/2504.04915)
- Apri 4 [Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-Generation](https://arxiv.org/pdf/2504.03165)
- Apri 3 [HyperRAG: Enhancing Quality-Efficiency Tradeoffs in Retrieval-Augmented Generation with Reranker KV-Cache Reuse](https://arxiv.org/pdf/2504.02921)
- Apri 3 [Scaling Test-Time Inference with Policy-Optimized, Dynamic Retrieval-Augmented Generation via KV Caching and Decoding](https://arxiv.org/pdf/2504.01281)
- Apri 1 [CoRanking: Collaborative Ranking with Small and Large Ranking Agents](https://arxiv.org/pdf/2503.23427)
### 🍭2025 March
- Mar 31 [Insight-RAG: Enhancing LLMs with Insight-Driven Augmentation](https://arxiv.org/pdf/2504.00187)
- Mar 31 [UltraRAG: A Modular and Automated Toolkit for Adaptive Retrieval-Augmented Generation](https://arxiv.org/pdf/2504.08761)
- Mar 31 [Better wit than wealth: Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement](https://arxiv.org/pdf/2503.23895)
- Mar 30 [RARE: Retrieval-Augmented Reasoning Modeling](https://arxiv.org/pdf/2503.23513)
- Mar 28 [Preference-based Learning with Retrieval Augmented Generation for Conversational Question Answering](https://arxiv.org/pdf/2503.22303)
- Mar 27 [ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented Generation](https://arxiv.org/pdf/2503.21729v1)
- Mar 23 [ExpertRAG: Efficient RAG with Mixture of Experts -- Optimizing Context Retrieval for Adaptive LLM Responses](https://arxiv.org/pdf/2504.08744)
- Mar 20 [Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Models](https://arxiv.org/abs/2503.15888)
- Mar 11 [OpenRAG: Optimizing RAG End-to-End via In-Context Retrieval Learning](https://arxiv.org/abs/2503.08398)
### 🍭2025 February
- Feb 26 [Judge as A Judge: Improving the Evaluation of Retrieval-Augmented Generation through the Judge-Consistency of Large Language Models](https://arxiv.org/pdf/2502.18817)
- Feb 25 [RankCoT: Refining Knowledge for Retrieval-Augmented Generation through Ranking Chain-of-Thoughts](https://arxiv.org/pdf/2502.17888)
- Feb 25 [Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation](https://arxiv.org/pdf/2502.17839)
- Feb 25 [DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers](https://arxiv.org/pdf/2502.18460)
- Feb 20 [Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering](https://arxiv.org/pdf/2502.14245)
- Feb 19 [RAG-Gym: Optimizing Reasoning and Search Agents with Process Supervision](https://arxiv.org/pdf/2502.13957)
- Feb 19 [Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach](https://arxiv.org/abs/2502.14100)
- Feb 19 [Towards Adaptive Memory-Based Optimization for Enhanced Retrieval-Augmented Generation](https://arxiv.org/pdf/2504.05312)
- Feb 18 [RAG-Reward: Optimizing RAG with Reward Modeling and RLHF](https://arxiv.org/pdf/2501.13264)
- Feb 17 [Revisiting Robust RAG: Do We Still Need Complex Robust Training in the Era of Powerful LLMs?](https://www.arxiv.org/pdf/2502.11400)
- Feb 16 [RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization](https://arxiv.org/pdf/2502.10993)
- Feb 14 [Post-training an LLM for RAG? Train on Self-Generated Demonstrations](https://arxiv.org/pdf/2502.10596)
- Feb 3 [DeepRAG: Thinking to Retrieval Step by Step for Large Language Models](https://arxiv.org/pdf/2502.01142)
### 🍭2025 January
- Jan 30 [Can we Retrieve Everything All at Once? ARM: An Alignment-Oriented LLM-based Retrieval Method](https://arxiv.org/pdf/2501.18539)
- Jan 30 [RbFT: Robust Fine-tuning for Retrieval-Augmented Generation against Retrieval Defects](https://arxiv.org/pdf/2501.18365)
- Jan 27 [Parametric Retrieval Augmented Generation](https://arxiv.org/pdf/2501.15915)
- Jan 14 [ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding](https://arxiv.org/pdf/2501.07861)
- Jan 9 [SUGAR: Leveraging Contextual Confidence for Smarter Retrieval](https://arxiv.org/pdf/2501.04899)
- Jan 7 [Retrieval-Augmented Generation by Evidence Retroactivity in LLMs](https://arxiv.org/pdf/2501.05475)
- Jan 2 [Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks](https://arxiv.org/pdf/2407.09893)
## 🥇ICML 2025
- [From RAG to Memory: Non-Parametric Continual Learning for Large Language Models](https://arxiv.org/pdf/2502.14802)
- [LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs -- No Silver Bullet for LC or RAG Routing](https://arxiv.org/pdf/2502.09977)
- [RAGGED: Towards Informed Design of Retrieval Augmented Generation Systems](https://arxiv.org/pdf/2403.09040)
- [DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt Tuning](https://openreview.net/pdf?id=SVl9tIADWV)
- [Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification](https://arxiv.org/pdf/2504.04578)
- [On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains](https://arxiv.org/pdf/2409.17275)
- [C-3PO: Compact Plug-and-Play Proxy Optimization to Achieve Human-like Retrieval-Augmented Generation](https://arxiv.org/pdf/2502.06205)
- [Long-Context Inference with Retrieval-Augmented Speculative Decoding](https://arxiv.org/pdf/2502.20330)
- [Position: Retrieval-augmented systems are currently dangerous medical communicators](https://arxiv.org/pdf/2502.14898v1)
## 🥇ICLR 2025
- [SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction](https://openreview.net/pdf?id=ixMBnOhFGd)
- [Inference Scaling for Long-Context Retrieval Augmented Generation](https://arxiv.org/pdf/2410.04343)
- [Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse](https://arxiv.org/pdf/2409.11242)
- [Sufficient Context: A New Lens on Retrieval Augmented Generation Systems](https://arxiv.org/pdf/2411.06037)
- [Enhancing Large Language Models' Situated Faithfulness to External Contexts](https://arxiv.org/pdf/2410.14675)
- [RAG-SR: Retrieval-Augmented Generation for Neural Symbolic Regression](https://openreview.net/pdf?id=NdHka08uWn)
- [SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback](https://arxiv.org/pdf/2410.18141)
- [InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales](https://arxiv.org/pdf/2406.13629)
- [RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards](https://arxiv.org/pdf/2410.13509)
- [TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models](https://arxiv.org/pdf/2405.13401)
- [Provence: efficient and robust context pruning for retrieval-augmented generation](https://arxiv.org/pdf/2501.16214)
- [Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG](https://arxiv.org/pdf/2410.05983)
- [LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory](https://arxiv.org/pdf/2410.10813)
- [MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models](https://arxiv.org/pdf/2410.13085v1)
- [A Theory for Token-Level Harmonization in Retrieval-Augmented Generation](https://arxiv.org/pdf/2406.00944v2)
- [SiReRAG: Indexing Similar and Related Information for Multihop Reasoning](https://arxiv.org/pdf/2412.06206)
- [VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents](https://arxiv.org/pdf/2410.10594)
- [ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability](https://arxiv.org/pdf/2410.11414)
- [ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities](https://arxiv.org/pdf/2407.14482)
- [Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection](https://arxiv.org/pdf/2405.16178)
- [Retrieval or Reasoning: The Roles of Graphs and Large Language Models in Efficient Knowledge-Graph-Based Retrieval-Augmented Generation](https://arxiv.org/pdf/2410.20724)
- [Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation](https://arxiv.org/pdf/2407.10805)
- [DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints](https://openreview.net/pdf?id=s9zoyICZ4k)
- [RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models](https://openreview.net/pdf?id=txZVQRc2ab)
- [Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation](https://arxiv.org/pdf/2410.03461)
- [Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting](https://arxiv.org/pdf/2407.08223)
- [Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems](https://arxiv.org/pdf/2402.17840)
- [Chunk-Distilled Language Modeling](https://arxiv.org/pdf/2501.00343)
- [Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent](https://arxiv.org/pdf/2411.02937)
## 🥇NIPS 2024
- [RAGraph: A General Retrieval-Augmented Graph Learning Framework](https://arxiv.org/pdf/2410.23855)
- [RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation](https://arxiv.org/pdf/2408.08067)
- [G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering](https://arxiv.org/abs/2402.07630)
- [RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs](https://arxiv.org/pdf/2407.02485)
- [ChatQA: Surpassing GPT-4 on Conversational QA and RAG](https://arxiv.org/pdf/2401.10225)
- [HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models](https://arxiv.org/pdf/2405.14831)
- [BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://arxiv.org/pdf/2406.10149)
- [Self-Retrieval: End-to-End Information Retrieval with One Large Language Model](https://arxiv.org/abs/2403.00801)
- [UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-World Document Analysis](https://arxiv.org/pdf/2406.15187)
- [Ad Auctions for LLMs via Retrieval Augmented Generation](https://arxiv.org/pdf/2406.09459)
- [ReFIR: Grounding Large Restoration Models with Retrieval Augmentation](https://arxiv.org/pdf/2410.05601)
- [TableRAG: Million-Token Table Understanding with Language Models](https://arxiv.org/pdf/2410.04739)
- [xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token](https://arxiv.org/pdf/2405.13792)
- [Scaling Retrieval-Based Language Models with a Trillion-Token Datastore](https://arxiv.org/pdf/2407.12854)
- [Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond](https://arxiv.org/pdf/2407.10005)
- [Molecule Generation with Fragment Retrieval Augmentation](https://arxiv.org/pdf/2411.12078)
- [WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia](https://arxiv.org/pdf/2406.13805)
- [Beyond Prompts: Dynamic Conversational Benchmarking of Large Language Models](https://arxiv.org/pdf/2409.20222)
- [ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLMs](https://arxiv.org/pdf/2408.12076)
- [CRAG - Comprehensive RAG Benchmark](https://arxiv.org/pdf/2406.04744)
### 🍭2024 December
- Dec 19 [PA-RAG: RAG Alignment via Multi-Perspective Preference Optimization](https://arxiv.org/pdf/2412.14510)
- Dec 11 [DADIO: Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation](https://arxiv.org/pdf/2412.08519)
- Dec 3 [RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Models](https://arxiv.org/pdf/2412.02830)
### 🍭2024 November
- Nov 1 [CORAG: A Cost-Constrained Retrieval Optimization System for Retrieval-Augmented Generation](https://arxiv.org/pdf/2411.00744)
### 🍭2024 October
- Oct 12 [Toward General Instruction-Following Alignment for Retrieval-Augmented Generation](https://arxiv.org/pdf/2410.09584)
- Oct 11 [STRUCTRAG: BOOSTING KNOWLEDGE INTENSIVE REASONING OF LLMS VIA INFERENCE-TIME HYBRID INFORMATION STRUCTURIZATION](https://arxiv.org/pdf/2410.08815)
- Oct 11 [Retriever-and-Memory: Towards Adaptive Note-Enhanced Retrieval-Augmented Generation](https://arxiv.org/pdf/2410.08821)
- Oct 9 [Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models](https://arxiv.org/pdf/2410.07176v1)
- Oct 7 [TableRAG: Million-Token Table Understanding with Language Models](https://arxiv.org/pdf/2410.04739)
- Oct 6 [Inference Scaling for Long-Context Retrieval Augmented Generation](https://arxiv.org/pdf/2410.04343)
- Oct 4 [How Much Can RAG Help the Reasoning of LLM?](https://arxiv.org/pdf/2410.02338)
- Oct 2[OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs](https://arxiv.org/pdf/2409.05152)
- Oct 2 [OPEN-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models](https://arxiv.org/pdf/2410.01782)
### 🍭2024 September
- Sep 23 [Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely](https://arxiv.org/pdf/2409.14924)
- Sep 4 [Diversify-verify-adapt: Efficient and Robust Retrieval-Augmented Ambiguous Question Answering](https://arxiv.org/pdf/2409.02361)
### 🍭2024 August
- Aug 30 [MaFeRw: Query Rewriting with Multi-Aspect Feedbacks for Retrieval-Augmented Large Language Models](https://arxiv.org/pdf/2408.17072v1)
- Aug 29 [LRP4RAG: Detecting Hallucinations in Retrieval-Augmented Generation via Layer-wise Relevance Propagation](https://arxiv.org/pdf/2408.15533v2)
- Aug 21 [RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation](https://arxiv.org/pdf/2408.11381)
- Aug 21 [Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMs](https://arxiv.org/abs/2408.12060)
- Aug 20 [Analysis of Plan-based Retrieval for Grounded Text Generation](https://arxiv.org/pdf/2408.10490)
- Aug 20 [Hierarchical Retrieval-Augmented Generation Model with Rethink for Multi-hop Question Answering](https://arxiv.org/abs/2408.11875)
- Aug 19 [KaPO: Knowledge-aware Preference Optimization for Controllable Knowledge Selection in Retrieval-Augmented Language Models](https://arxiv.org/pdf/2408.03297)
- Aug 17 [TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems](https://arxiv.org/abs/2408.09199)
- Aug 16 [Meta Knowledge for Retrieval Augmented Large Language Models](https://arxiv.org/abs/2408.09017)
- Aug 7 [EfficientRAG: Efficient Retriever for Multi-Hop Question Answering](https://arxiv.org/pdf/2408.04259)
- Aug 7 [Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation](https://arxiv.org/pdf/2408.04187)
- Aug 7 [Exploring RAG-based Vulnerability Augmentation with LLMs](https://arxiv.org/pdf/2408.04125)
- Aug 7 [Wiping out the limitations of Large Language Models -- A Taxonomy for Retrieval Augmented Generation](https://arxiv.org/pdf/2408.02854)
- Aug 2 [BioRAG: A RAG-LLM Framework for Biological Question Reasoning](https://arxiv.org/pdf/2408.01107)
- Aug 2 [Adaptive Contrastive Decoding in Retrieval-Augmented Generation for Handling Noisy Contexts](https://arxiv.org/pdf/2408.01084)
### 🍭2024 July
- Jul 29 [Improving Retrieval Augmented Language Model with Self-Reasoning](https://arxiv.org/pdf/2407.19813)
- Jul 29 [Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation](https://arxiv.org/pdf/2407.19619)
- Jul 28 [Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation](https://arxiv.org/pdf/2407.19619)
- Jul 25 [Modular RAG: Transforming RAG Systems into LEGO-like Reconfigurable Frameworks](https://arxiv.org/pdf/2407.21059)
- Jul 20 [Golden-Retriever: High-Fidelity Agentic Retrieval Augmented Generation for Industrial Knowledge Base](https://arxiv.org/pdf/2408.00798)
- Jul 19 [RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering](https://arxiv.org/pdf/2407.13998)
- Jul 17 [Optimizing Query Generation for Enhanced Document Retrieval in RAG](https://arxiv.org/pdf/2407.12325)
- Jul 11 [Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting](https://arxiv.org/pdf/2407.08223?trk=public_post_comment-text)
- jul 2 [RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs](https://arxiv.org/pdf/2407.02485)
- Jul 1 [Searching for Best Practices in Retrieval-Augmented Generation](https://arxiv.org/pdf/2407.01219?trk=public_post_comment-text)
### 🍭2024 June
- Jun 29 [From RAG to RICHES:Retrieval Interlaced with Sequence Generation](https://arxiv.org/pdf/2407.00361)
- Jun 27 [SEAKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Genaration](https://arxiv.org/pdf/2406.19215)
- Jun 27 [Unified Active Retrieval for Retrieval Augmented Generation](https://arxiv.org/pdf/2406.12534)
- Jun 27 [CrAM: Credibility-Aware Attention Modification in LLMs for Combating Misinformation in RAG](https://arxiv.org/pdf/2406.11497)
- Jun 25 [Entropy-Based Decoding for Retrieval-Augmented Large Language Models](https://arxiv.org/pdf/2406.17519)
- Jun 21 [RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation](https://arxiv.org/pdf/2406.12566)
- Jun 21 [LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs](https://arxiv.org/pdf/2406.15319?fbclid=IwZXh0bgNhZW0CMTAAAR0kiZE83xw45pTDrykhxRUoIkFJJecrR09nDIFd_M96h9_RCCqp04mvx44_aem_vvI_bJ5zlcSTvbdAcAUPZA)
- Jun 19 [R2AG: Incorporating Retrieval Information into Retrieval Augmented Generation](https://arxiv.org/pdf/2406.13249)
- Jun 19 [INSTRUCTRAG: Instructing Retrieval-Augmented Generation with Explicit Denoising](https://arxiv.org/pdf/2406.13629)
- Jun 18 [Retrieve, Summarize, Plan: Advancing Multi-hop Question Answering with an Iterative Approach](https://arxiv.org/pdf/2407.13101)
- Jun 18 [PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers](https://arxiv.org/pdf/2406.12430)
- Jun 18 [Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding](https://arxiv.org/pdf/2406.12331)
- Jun 12 [Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation](https://arxiv.org/pdf/2402.18150)
- Jun 7 [Multi-Head RAG: Solving Multi-Aspect Problems with LLMs](https://arxiv.org/pdf/2406.05085?trk=public_post_comment-text)
- Jun 7 [CRAG - Comprehensive RAG Benchmark](https://arxiv.org/pdf/2406.04744)
- Jun 1 [Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation](https://arxiv.org/pdf/2406.00456)
### 🍭2024 May
- May 30 [GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning](https://arxiv.org/pdf/2405.20139)
- May 26 [Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration](https://arxiv.org/pdf/2405.16546)
- May 23 [HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models](https://arxiv.org/pdf/2405.14831)
- May 22 [xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token](https://arxiv.org/pdf/2405.13792)
- May 14 [ERATTA: Extreme RAG for Table To Answers with Large Language Models](https://arxiv.org/pdf/2405.03963)
- May 13 [Evaluation of Retrieval-Augmented Generation: A Survey](https://arxiv.org/pdf/2405.07437)
- May 12 [DUETRAG: COLLABORATIVE RETRIEVAL-AUGMENTEDGENERATION](https://arxiv.org/pdf/2405.13002)
- May 6 [ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization](https://arxiv.org/pdf/2405.06683)
### 🍭2024 April
- Apr 26 [Better Synthetic Data by Retrieving and Transforming Existing Datasets](https://arxiv.org/pdf/2404.14361)
- Apr 22 [LLMs Know What They Need: Leveraging a Missing Information Guided Framework to Empower Retrieval-Augmented Generation](https://arxiv.org/pdf/2404.14043)
- Apr 16 [How faithful are RAG models? Quantifying the tug-of-war between RAG and LLMs' internal prior](https://arxiv.org/pdf/2404.10198?trk=public_post_comment-text)
- Apr 12 [Reducing hallucination in structured outputs via Retrieval-Augmented Generation](https://arxiv.org/pdf/2404.08189)
- Apr 1 [ARAGOG: Advanced RAG Output Grading](https://arxiv.org/pdf/2404.01037.pdf?trk=public_post_comment-text)
### 🍭2024 March
- Mar 21 [FIT-RAG: Black-Box RAG with Factual Information and Token Reduction](https://arxiv.org/pdf/2403.14374)
- Mar 15 [RAFT: Adapting Language Model to Domain Specific RAG](https://arxiv.org/pdf/2403.10131?trk=public_post_comment-text)
- Mar 14 [G-Retriever: Retrieval-AugmeAprnted Generation for Textual Graph Understanding and Question Answering](https://arxiv.org/pdf/2402.07630)
- Mar 8 [RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation](https://arxiv.org/pdf/2403.05313v1?trk=public_post_comment-text)
### 🍭2024 February
- Feb 27 [REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering](https://arxiv.org/pdf/2402.17497)
- Feb 22 [Tug-of-War Between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models](https://arxiv.org/pdf/2402.14409)
- Feb 21 [ACTIVERAG: Revealing the Treasures of Knowledge via Active Learning](https://arxiv.org/pdf/2402.13547)
- Feb 16 [Retrieve Only When It Needs: Adaptive Retrieval Augmentation for Hallucination Mitigation in Large Language Models](https://arxiv.org/pdf/2402.10612)
- Feb 16 [Corrective Retrieval Augmented Generation](https://arxiv.org/pdf/2401.15884)
### 🍭2024 January
- Jan 27 [Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately](https://arxiv.org/pdf/2402.01722)
- Jan 24 [UniMS-RAG: A Unified Multi-source Retrieval-Augmented Generation for Personalized Dialogue Systems](https://arxiv.org/pdf/2401.13256)
### 🥇EMNLP 2024
$main$
- [BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering](https://aclanthology.org/2024.emnlp-main.58.pdf)
- [“Glue pizza and eat rocks” - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models](https://aclanthology.org/2024.emnlp-main.96.pdf)
- [SEER: Self-Aligned Evidence Extraction for Retrieval-Augmented Generation](https://aclanthology.org/2024.emnlp-main.178.pdf)
- [Crafting Personalized Agents through Retrieval-Augmented Generation on Editable Memory Graphs](https://aclanthology.org/2024.emnlp-main.281.pdf)
- [REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering](https://aclanthology.org/2024.emnlp-main.321.pdf)
- [Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation](https://aclanthology.org/2024.emnlp-main.347.pdf)
- [TimeR4 : Time-aware Retrieval-Augmented Large Language Models for Temporal Knowledge Graph Question Answering](https://aclanthology.org/2024.emnlp-main.394.pdf)
- [Synchronous Faithfulness Monitoring for Trustworthy Retrieval-Augmented Generation](https://aclanthology.org/2024.emnlp-main.527.pdf)
- [ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator](https://aclanthology.org/2024.emnlp-main.610.pdf)
- [Lifelong Knowledge Editing for LLMs with Retrieval-Augmented Continuous Prompt Learning](https://aclanthology.org/2024.emnlp-main.751.pdf)
- [Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models](https://aclanthology.org/2024.emnlp-main.813.pdf)
- [Searching for Best Practices in Retrieval-Augmented Generation](https://aclanthology.org/2024.emnlp-main.981.pdf)
- [Unveiling and Consulting Core Experts in Retrieval-Augmented MoE-based LLMs](https://aclanthology.org/2024.emnlp-main.993.pdf)
- [RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented Generation](https://aclanthology.org/2024.emnlp-main.1236.pdf)
- [LongRAG: A Dual-perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering](https://aclanthology.org/2024.emnlp-main.1259.pdf)
- [ZEBRA: Zero-Shot Example-Based Retrieval Augmentation for Commonsense Question Answering](https://aclanthology.org/2024.emnlp-main.1251.pdf)
- [RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models](https://aclanthology.org/2024.emnlp-main.62.pdf)
- [From RAG to Riches: Retrieval Interlaced with Sequence Generation](https://aclanthology.org/2024.emnlp-main.502.pdf)
- [Summary of a Haystack: A Challenge to Long-Context LLMs and RAG Systems](https://aclanthology.org/2024.emnlp-main.552.pdf)
- [Deciphering the Interplay of Parametric and Non-Parametric Memory in RAG Models](https://aclanthology.org/2024.emnlp-main.943.pdf)
- [DynamicER: Resolving Emerging Mentions to Dynamic Entities for RAG](https://aclanthology.org/2024.emnlp-main.762.pdf)
- [RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering](https://aclanthology.org/2024.emnlp-main.249.pdf)
- [Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation](https://aclanthology.org/2024.emnlp-main.353.pdf)
$fingdings$
- [RaFe: Ranking Feedback Improves Query Rewriting for RAG](https://aclanthology.org/2024.findings-emnlp.49.pdf)
- [Adaptive Contrastive Decoding in Retrieval-Augmented Generation for Handling Noisy Contexts](https://aclanthology.org/2024.findings-emnlp.136.pdf)
- [BSharedRAG: Backbone Shared Retrieval-Augmented Generation for the E-commerce Domain](https://aclanthology.org/2024.findings-emnlp.62.pdf)
- [LONG2RAG: Evaluating Long-Context & Long-Form Retrieval-Augmented Generation with Key Point Recall](https://aclanthology.org/2024.findings-emnlp.279.pdf)
- [Open-RAG: Enhanced Retrieval Augmented Reasoning with Open-Source Large Language Models](https://aclanthology.org/2024.findings-emnlp.831.pdf)
- [TRACE the Evidence: Constructing Knowledge-Grounded Reasoning Chains for Retrieval-Augmented Generation](https://aclanthology.org/2024.findings-emnlp.496.pdf)
- [BERGEN: A Benchmarking Library for Retrieval-Augmented Generation](https://aclanthology.org/2024.findings-emnlp.449.pdf)
- [Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs](https://aclanthology.org/2024.findings-emnlp.459.pdf)
- [Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft](https://aclanthology.org/2024.findings-emnlp.652.pdf)
- [“Knowing When You Don’t Know”: A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented Generation](https://aclanthology.org/2024.findings-emnlp.730.pdf)
- [LLMs as Collaborator: Demands-Guided Collaborative Retrieval-Augmented Generation for Commonsense Knowledge-Grounded Open-Domain Dialogue Systems](https://aclanthology.org/2024.findings-emnlp.794.pdf)
- [Retrieving, Rethinking and Revising: The Chain-of-Verification Can Improve Retrieval Augmented Generation](https://aclanthology.org/2024.findings-emnlp.607.pdf)
- [R2AG: Incorporating Retrieval Information into Retrieval Augmented Generation](https://aclanthology.org/2024.findings-emnlp.678.pdf)
- [RAG-Studio: Towards In-Domain Adaptation Of Retrieval Augmented Generation Through Self-Alignment](https://aclanthology.org/2024.findings-emnlp.41.pdf)
- [Unified Active Retrieval for Retrieval Augmented Generation](https://aclanthology.org/2024.findings-emnlp.999.pdf)
- [SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation](https://aclanthology.org/2024.findings-emnlp.71.pdf)
- [Controlling Risk of Retrieval-augmented Generation: A Counterfactual Prompting Framework](https://aclanthology.org/2024.findings-emnlp.133.pdf)
- [AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation](https://aclanthology.org/2024.findings-emnlp.223.pdf)
- [Typos that Broke the RAG’s Back: Genetic Attack on RAG Pipeline by Simulating Documents in the Wild via Low-level Perturbations](https://aclanthology.org/2024.findings-emnlp.161.pdf)
### 🥇ACL 2024
$main$
- [Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation](https://arxiv.org/pdf/2402.18150)
- [An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation](https://arxiv.org/pdf/2406.01549)
- [Bridging the Preference Gap between Retrievers and LLMs](https://arxiv.org/pdf/2401.06954)
- [ARL2: Aligning Retrievers with Black-box Large Language Models via Self-guided Adaptive Relevance Labeling](https://arxiv.org/pdf/2402.13542)
- [M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions](https://arxiv.org/pdf/2405.16420)
- [Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering](https://arxiv.org/pdf/2406.14891)
- [Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training](https://arxiv.org/pdf/2405.20978)
- [RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models](https://arxiv.org/pdf/2401.00396)
- [Grounding Language Model with Chunking-Free In-Context Retrieval](https://arxiv.org/pdf/2402.09760)
- [On the Role of Long-tail Knowledge in Retrieval Augmented Large Language Models](https://arxiv.org/pdf/2406.16367)
- [Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models](https://arxiv.org/pdf/2402.11573)
- [A Multi-Task Embedder For Retrieval Augmented LLM](https://aclanthology.org/2024.acl-long.194.pdf)
- [To Generate or to Retrieve? On the Effectiveness of Artificial Contexts for Medical Open-Domain Question Answering](https://arxiv.org/pdf/2403.01924)
- [Blinded by Generated Contexts: How Language Models Merge Generated and Retrieved Contexts When Knowledge Conflicts?](https://arxiv.org/pdf/2401.11911)
- [Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs](https://arxiv.org/pdf/2402.12052)
- [RAM-EHR: Retrieval Augmentation Meets Clinical Predictions on Electronic Health Records](https://arxiv.org/pdf/2403.00815)
- [DRAGIN: Dynamic Retrieval Augmented Generation based on the Real-time Information Needs of Large Language Models](https://arxiv.org/pdf/2403.10081)
- [Retrieval Augmented Fact Verification by Synthesizing Contrastive Arguments](https://arxiv.org/pdf/2406.09815)
- [Dataflow-Guided Retrieval Augmentation for Repository-Level Code Completion](https://arxiv.org/pdf/2405.19782)
- [Understanding Retrieval Robustness for Retrieval-augmented Image Captioning](https://arxiv.org/pdf/2406.02265)
- [Spiral of Silence: How is Large Language Model Killing Information Retrieval?—A Case Study on Open Domain Question Answering](https://arxiv.org/pdf/2404.10496)
- [REANO: Optimising Retrieval-Augmented Reader Models through Knowledge Graph Generation](https://aclanthology.org/2024.acl-long.115.pdf)
- [Synergistic Interplay between Search and Large Language Models for Information Retrieval](https://arxiv.org/pdf/2305.07402)
$findings$
- [MORE: Multi-mOdal REtrieval Augmented Generative Commonsense Reasoning](https://aclanthology.org/2024.findings-acl.69.pdf)
- [RA-ISF: Learning to Answer and Understand from Retrieval Augmentation via Iterative Self-Feedback](https://aclanthology.org/2024.findings-acl.281.pdf)
- [Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized Contexts](https://aclanthology.org/2024.findings-acl.458.pdf)
- [When Do LLMs Need Retrieval Augmentation? Mitigating LLMs’ Overconfidence Helps Retrieval Augmentation](https://aclanthology.org/2024.findings-acl.675.pdf)
- [RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering](https://aclanthology.org/2024.findings-acl.415.pdf)
- [Retrieval-Augmented Retrieval: Large Language Models are Strong Zero-Shot Retriever](https://aclanthology.org/2024.findings-acl.943.pdf)
- [Benchmarking Retrieval-Augmented Generation for Medicine](https://aclanthology.org/2024.findings-acl.372.pdf)
- [Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models](https://aclanthology.org/2024.findings-acl.288.pdf)
- [ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models](https://aclanthology.org/2024.findings-acl.122.pdf)
- [The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)](https://aclanthology.org/2024.findings-acl.267.pdf)
### 🥇ICML 2024
- [C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models](https://arxiv.org/pdf/2402.03181)
- [DFA-RAG: Conversational Semantic Router for Large Language Model with Definite Finite Automaton](https://openreview.net/pdf?id=LpAzlcGzJ6)
- [InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining](https://arxiv.org/pdf/2310.07713)
- [A Statistical Framework for Data-dependent Retrieval-Augmented Models](https://arxiv.org/pdf/2408.15399)
- [Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation](https://arxiv.org/pdf/2404.06910)
- [Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learning](https://openreview.net/pdf?id=XwnABAdH5y)
- [Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models](https://arxiv.org/pdf/2405.01468)
- [Bottleneck-Minimal Indexing for Generative Document Retrieval](https://arxiv.org/pdf/2405.10974)
- [PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation](https://openreview.net/pdf?id=TqcZfMZjgM)
- [Retrieval-Augmented Score Distillation for Text-to-3D Generation](https://arxiv.org/pdf/2402.02972)
- [Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation](https://arxiv.org/pdf/2405.13622)
- [Accelerating Iterative Retrieval-augmented Language Model Serving with Speculation](https://openreview.net/pdf?id=CDnv4vg02f)
### 🥇ICLR 2024
- [Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection](https://arxiv.org/pdf/2310.11511)
- [BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models](https://arxiv.org/pdf/2310.01329)
- [Making Retrieval-Augmented Language Models Robust to Irrelevant Context](https://arxiv.org/pdf/2310.01558)
- [RA-DIT: Retrieval-Augmented Dual Instruction Tuning](https://arxiv.org/pdf/2310.01352?trk=public_post_comment-text)
- [RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval](https://arxiv.org/pdf/2401.18059.pdf?utm_referrer=https%3A%2F%2Fdzen.ru%2Fmedia%2Fid%2F5e048b1b2b616900b081f1d9%2F66110fe915ffb223365956df)
- [RECOMP: Improving Retrieval-Augmented LMs with Context Compression and Selective Augmentation](https://openreview.net/pdf?id=mlJLVigNHp)
- [Retrieval meets Long Context Large Language Models](https://arxiv.org/pdf/2310.03025)
- [SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs](https://arxiv.org/pdf/2404.13081)
## Star History
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