Retrieval-Augmented Generation

Also known as RAG

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49 papers in the last four weeks, up 36% on the four weeks before. 0.5% of all new papers.

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Event-Causal RAG: A Retrieval-Augmented Generation Framework for Long Video Reasoning in Complex Scenarios
May 7, 2026Peizheng Yan, Yu Zhao, Liang Xie +3Retrieval-Augmented Generation Streaming Video Understanding
Tianjin Key Lab of Intelligent Unmanned Swarm Tech & System Tianjin University Tianjin, China · Institute of Computing and Intelligence Harbin Institute of Technology (Shenzhen) Shenzhen, China · Tianjin Artificial Intelligence Innovation Center Tianjin, China +2
Retrieval from Within: An Intrinsic Capability of Attention-Based Models
May 7, 2026Elad Hoffer, Yochai Blau, Edan Kinderman +3Retrieval-Augmented Generation Question Answering
NVIDIA · Department of Electrical Engineering, Technion, Haifa, Israel
Text-Graph Synergy: A Bidirectional Verification and Completion Framework for RAG
May 7, 2026Jiarui Zhong, Hong Cai ChenRetrieval-Augmented Generation Graph Retrieval-Augmented Generation
School of Automation, Southeast University, Nanjing 210096, China
Architecture Matters: Comparing RAG Systems under Knowledge Base Poisoning
May 7, 2026Samuel KornRetrieval-Augmented Generation RAG Poisoning Attacks
Privacy Without Losing Place: A Paradigm for Private Retrieval in Spatial RAGs
May 6, 2026Kennedy Edemacu, Mohammad Mahdi Shokri, Vinay M. Shashidhar +1Retrieval-Augmented Generation Privacy-Preserving ML
The City University of New York, College of Staten Island and Graduate Center · The City University of New York, Graduate Center · Northern Michigan University +1
CAR: Query-Guided Confidence-Aware Reranking for Retrieval-Augmented Generation
May 6, 2026Zhipeng Song, Yizhi Zhou, Xiangyu Kong +6Retrieval-Augmented Generation Learning to Rank
School of Computer Science and Technology, Dalian University of Technology, No.2 Linggong Road, Ganjingzi District, Dalian, 116024, China · School of Information Engineering, Dalian Ocean University, No. 2-52, Heishijiao Street, Shahekou District, Dalian, 116023, China · School of Information Engineering, Liaodong University, No.116 Linjiang Back Street, Zhenan District, Dandong, 118001, China +3
Career-Aware Resume Tailoring via Multi-Source Retrieval-Augmented Generation with Provenance Tracking: A Case Study
May 6, 2026Kumar AbhinavRetrieval-Augmented Generation Agentic RAG
Safety and accuracy follow different scaling laws in clinical large language models
May 5, 2026Sebastian Wind, Tri-Thien Nguyen, Jeta Sopa +9LLM Safety Benchmarks Retrieval-Augmented Generation
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Institute of Radiology, University Hospital Erlangen, Erlangen, Germany · Lab for AI in Medicine, RWTH Aachen University, Aachen, Germany +3
SURE-RAG: Sufficiency and Uncertainty-Aware Evidence Verification for Selective Retrieval-Augmented Generation
May 5, 2026Jingxi Qiu, Zeyu Han, Cheng HuangRetrieval-Augmented Generation LLM Answer Verification
ZenWeave AI · Georgetown University · Southern Methodist University
RAG over Thinking Traces Can Improve Reasoning Tasks
May 5, 2026Negar Arabzadeh, Wenjie Ma, Sewon Min +1Retrieval-Augmented Generation LLM Mathematical Reasoning
University of California, Berkeley
SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction
May 4, 2026Sin Yu Bonnie Ho, Arlie Coles, Erik Larsson +3Retrieval-Augmented Generation LLM Inference Acceleration
Microsoft
AdaGATE: Adaptive Gap-Aware Token-Efficient Evidence Assembly for Multi-Hop Retrieval-Augmented Generation
May 4, 2026Yilin Guo, Yinshan Wang, Yixuan WangMulti-Hop QA Retrieval-Augmented Generation
Center for Data Science New York University · Tandon School of Engineering New York University
Benchmarking Retrieval Strategies for Biomedical Retrieval-Augmented Generation: A Controlled Empirical Study
May 4, 2026Devi Prasad Bal, Subhashree PuhanCross-Encoder Reranking Retrieval-Augmented Generation
The University of Texas at Austin
Towards Dependable Retrieval-Augmented Generation Using Factual Confidence Prediction
May 4, 2026Florian Geissler, Francesco Carella, Laura Fieback +1Retrieval-Augmented Generation Factual Consistency Evaluation
Fraunhofer Institute for Cognitive Systems (IKS), Munich, Germany · Volkswagen AG, Wolfsburg, Germany
AutoRAGTuner: A Declarative Framework for Automatic Optimization of RAG Pipelines
May 3, 2026Xintan Zeng, Yongchao Liu, Yice Luo +1Retrieval-Augmented Generation
Ant Group, China
FT-RAG: A Fine-grained Retrieval-Augmented Generation Framework for Complex Table Reasoning
May 2, 2026Zebin Guo, Weidong Geng, Ruichen MaoMultimodal RAG Table QA
Georgia Institute of Technology Atlanta, Georgia, USA · Zhejiang University Hangzhou, Zhejiang, China · Zhejiang Lab Hangzhou, Zhejiang, China
Verbal-R3: Verbal Reranker as the Missing Bridge between Retrieval and Reasoning
May 2, 2026Sangkwon Park, Donghun Kang, Jisoo Mok +1Retrieval-Augmented Generation LLM Reranking
Department of Electrical and Computer Engineering, Seoul National University · DGIST · Interdisciplinary Program in Artificial Intelligence, Seoul National University +1
Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation
May 2, 2026Peiyang Liu, Qiang Yan, Ziqiang Cui +3Retrieval-Augmented Generation LLM Hallucination Mitigation
National Engineering Research Center for Software Engineering, Peking University Beijing, China · PX Securities Shenzhen, China · City University of Hong Kong Hong Kong SAR, China +2
Chain of Evidence: Pixel-Level Visual Attribution for Iterative Retrieval-Augmented Generation
May 2, 2026Peiyang Liu, Ziqiang Cui, Xi Wang +2Retrieval-Augmented Generation Vision-Language Grounding
National Engineering Research Center for Software Engineering, Peking University Beijing, China · City University of Hong Kong Hong Kong SAR, China · Tencent Technology Beijing, China
BlenderRAG: High-Fidelity 3D Object Generation via Retrieval-Augmented Code Synthesis
May 1, 2026Massimo Rondelli, Francesco Pivi, Maurizio GabbrielliRetrieval-Augmented Generation 3D Asset Generation
University of Bologna, Bologna, Italy · Ferrari S.p.A., Maranello, Italy
H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversations
May 1, 2026Passant Elchafei, Hossam Emam, Mohamed Alansary +2Retrieval-Augmented Generation Information Retrieval
1Johannes Kepler University Linz, Institute of Computational Perception, Linz, Austria · 3Independent Researcher, Egypt · 2Linz Institute of Technology, Artificial Intelligence Lab, Austria
"I Don't Know" -- Towards Appropriate Trust with Certainty-Aware Retrieval Augmented Generation
May 1, 2026Daan Di Scala, Maaike de Boer, Pınar YolumRetrieval-Augmented Generation LLM Reliability
TNO Netherlands Organisation for Applied Scientific Research, Department Data Science · Utrecht University, Department of Information and Computing Sciences
Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation
May 1, 2026Ziwen Zhao, Menglin YangMulti-Hop QA Retrieval-Augmented Generation
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China.
VLADriver-RAG: Retrieval-Augmented Vision-Language-Action Models for Autonomous Driving
May 1, 2026Rui Zhao, Haofeng Hu, Zhenhai Gao +2Retrieval-Augmented Generation VLMs for Autonomous Driving
College of Automotive Engineering, Jilin University · The National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University · ReeFocus AI Technology
Structure-Aware Chunking for Tabular Data in Retrieval-Augmented Generation
May 1, 2026Pooja Guttal, Varun Magotra, Vasudeva Mahavishnu +3Document Chunking Retrieval-Augmented Generation
Altumatim · University of Maryland, Baltimore County
Retrieval-Augmented Reasoning for Chartered Accountancy
Apr 30, 2026Jatin Gupta, Akhil Sharma, Saransh Singhania +1Retrieval-Augmented Generation Financial QA
Dept. of Computer Science and Engineering Sharda University, Greater Noida, India · Sharda University, Greater Noida, India
NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains
Apr 30, 2026Shiyao Peng, Qianhe Zheng, Zhuodi Hao +7Multi-Hop QA Retrieval-Augmented Generation
Beijing University of Posts and Telecommunications
Iterative Multimodal Retrieval-Augmented Generation for Medical Question Answering
Apr 30, 2026Xupeng Chen, Binbin Shi, Chenqian Le +5Multimodal RAG Retrieval-Augmented Generation
New York University, New York, USA · Tsinghua University, Beijing, China · Independent Researcher +1
Decoupling Knowledge and Task Subspaces for Composable Parametric Retrieval Augmented Generation
Apr 29, 2026Weihang Su, Hanwen Zhang, Qingyao Ai +1Retrieval-Augmented Generation Low-Rank Adaptation
Department of Computer Science and Technology, Tsinghua University
When to Retrieve During Reasoning: Adaptive Retrieval for Large Reasoning Models
Apr 29, 2026Dongxin Guo, Jikun Wu, Siu Ming YiuRetrieval-Augmented Generation Multi-Hop Reasoning
The University of Hong Kong Hong Kong, China · Brain Investing Limited Hong Kong, China · Stellaris AI Limited Hong Kong, China

May 7, 2026, cs.AIJ/K move · Enter open · S save

Event-Causal RAG: A Retrieval-Augmented Generation Framework for Long Video Reasoning in Complex Scenarios

Peizheng Yan, Yu Zhao, Liang Xie, Juntong Qi+2

Tianjin Key Lab of Intelligent Unmanned Swarm Tech & System Tianjin University Tianjin, China · Institute of Computing and Intelligence Harbin Institute of Technology (Shenzhen) Shenzhen, China · Tianjin Artificial Intelligence Innovation Center Tianjin, China+2

Retrieval-Augmented Generation Streaming Video Understanding Long-Video Understanding Video Reasoning Long-Video QA Causal Reasoning in Videos

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Recent large vision-language models have achieved strong performance on short- and medium-length video understanding, yet they remain inadequate for ultra-long or even infinite video reasoning, where models must preserve coherent memory over extended durations and infer causal dependencies across temporally distant events. Existing end-to-end video understanding methods are fundamentally limited by the

O(n^2)

complexity of self-attention, while recent retrieval-augmented generation (RAG) approaches still suffer from fragmented clip-level memory, weak modeling of temporal and causal structure, and high storage and online inference costs. We present Event-Causal RAG, a lightweight retrieval-augmented framework for infinite long-video reasoning. Instead of indexing fixed-length clips, our method segments streaming videos into semantically coherent events and represents each event as a structured State-Event-State (SES) graph, capturing the event together with its surrounding state transitions. These graphs are merged into a global Event Knowledge Graph and stored in a dual-store memory that supports both semantic matching and causal-topological retrieval. On top of this memory, we design a bidirectional retrieval strategy to efficiently identify the most relevant event causal chains and provide them, together with the associated video evidence, to a backbone video foundation model for answer generation. Experiments on long-video understanding benchmarks demonstrate that Event-Causal RAG consistently outperforms strong clip-based retrieval baselines and long-context video models, particularly on questions requiring multi-event integration and causal inference across long temporal gaps, while also achieving improved memory efficiency and robust streaming performance.

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Latest papers 503