Agentic RAG

RAG: Retrieval-Augmented Generation

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15 papers in the last four weeks, up 88% on the four weeks before. 0.1% of all new papers.

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Latest papers 153

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Cascading Hallucination in Agentic RAG: The CHARM Framework for Detection and Mitigation
Jun 3, 2026Saroj MishraLLM Hallucination Mitigation Hallucination in Language Models
University of North Dakota
MemoGen: Can Past Experience Improve Future Text-to-Image Generation?
Jun 2, 2026Wenshuo Chen, Kuimou Yu, Bowen Tian +10T2I Generation Image Generation
The Hong Kong University of Science and Technology (Guangzhou) · Scholarly, Guangzhou Ziyan Technology Co., Ltd. · LimX Dynamics Technology Co., Ltd. +4
The Crowded Embedding Space: A Mean-Field Mechanism for Emergent Marginalization in Retrieval-Augmented Agents
Jun 1, 2026Shwan Ashrafi, Dan RothAlgorithmic Fairness Mean-Field Theory
Oracle AI
When Knowledge Is Not Free: Cost-Aware Evidence Selection in Retrieval-Augmented Generation
Jun 1, 2026Mingyan Wu, Han Yang, Omer Ben-Porat +1Retrieval-Augmented Generation Evidence Selection
Northeastern University · Technical University of Munich · GESIS – Leibniz Institute for the Social Sciences +3
TechRAG: Evidence-Gated Multimodal Agentic RAG for Technical Literature Reasoning
Jun 1, 2026Kanwar Bharat SinghMultimodal RAG Scientific QA
Global Tire Intelligence and Solutions (GTIS) The Goodyear Tire & Rubber Company
DrugClaw and DrugAudit: A Primary-Source-Grounded Agent and Authority-Aware Benchmark for Drug-Information Question Answering
May 31, 2026Qing Wang, Bo Li, Jialu Liang +3Biomedical QA Agentic RAG
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Florida, USA · PAMI Research Group, Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Taipa, Macau, China
ExpWeaver: LLM Agents Learn from Experience via Latent RAG
May 31, 2026Tao Feng, Tianyang Luo, Jingjun Xu +5Retrieval-Augmented Generation Agentic RAG
Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA · Meta Monetization AI, USA
SURGENT: A Surgical Multi-Agent Assistance System Across the Perioperative Workflow
May 28, 2026Dongsheng Shi, Yue Li, Xin Yi +3Multi-Agent LLM Systems Clinical Decision Support
East China Normal University Shanghai, China · City University of Hong Kong Hong Kong SAR, China
Plan Before Search: Search Agents Need Plan
May 27, 2026Zhipeng Qian, Zihan Liang, Yufei Ma +7Multi-Hop QA Tool-Augmented Language Model Agents
1Kuaishou Technology · 2Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, 361005, P.R. China · 3VCIP, CS, Nankai University
Natural Language Query to Configuration for Retrieval Agents
May 26, 2026Melissa Z. Pan, Negar Arabzadeh, Mathew Jacob +3Retrieval-Augmented Generation Cost-Aware Inference
UC Berkeley · University of Washington · Microsoft Azure Research - Systems
From Norms to Indicators (N2I-RAG): An Agentic Retrieval-Augmented Generation Framework for Legal Indicator Computation
May 26, 2026Youssef Al Mouatamid, Marie Bonnin, Jihad ZahirLegal Document Analysis Agentic RAG
LISI Laboratory, Cadi Ayyad University, Marrakesh, 40000, Morocco. · LEMAR, Univ Brest, Plouzane, F-29280, France. · IRD, Univ Brest, CNRS, Ifremer, LEMAR, Plouzane, F-29280, France. +1
Cordon-MAS: Defending RAG against Knowledge Poisoning via Information-Flow Control
May 26, 2026Zhe Yu, Wenpeng Xing, Gaolei Li +4RAG Poisoning Attacks Information Flow Control
Binjiang Institute of Zhejiang University · Zhejiang University · Shanghai Jiao Tong University +3
Experiments in Agentic AI for Science
May 25, 2026Judy Fox, Geoffrey FoxDocument Understanding AI for Science
School of Data Science, Department of Computer Science, and Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA.
Iterate Until Retrieved: Factual Nugget Optimization for Discoverable Continual Corrections in Agentic RAG
May 25, 2026Moshe Hazoom, Gal Patel, Alon Talmor +1Knowledge Editing Agentic RAG
Mosaic AI · The Hebrew University of Jerusalem
EfficientGraph-RAG: Structured Retrieval-State Management for Cross-Task Retrieval-Augmented Generation
May 25, 2026Miaohe Niu, Lianlei Shan, Zhengtao Yu +2Retrieval-Augmented Generation Graph Retrieval-Augmented Generation
School of Computer Science and Engineering, Northeastern University, China · 2Tsinghua University, China · 3Kunming University of Science and Technology, China +1
Tool-Schema Compression Enables Agentic RAG Under Constrained Context Budgets
May 24, 2026Furkan SakizliTool-Augmented Language Model Agents Agentic RAG
Independent Researcher
MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration
May 24, 2026Magnus Samuelsen, Wilmer Nyström, Somnath Mazumdar +2Financial Services Multi-Agent LLM Systems
Copenhagen Business School, Solbjerg Plads 3, Frederiksberg, 2000, Denmark · Jyske Bank, Copenhagen, Denmark
SpecHop: Continuous Speculation for Accelerating Multi-Hop Retrieval Agents
May 21, 2026Mehrdad Saberi, Keivan Rezaei, Soheil FeiziMulti-Hop QA Tool-Augmented Language Model Agents
University of Maryland, College Park
SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning
May 18, 2026Yufei Ma, Zihan Liang, Ben Chen +6On-Policy Self-Distillation RL for Language Model Reasoning
Kuaishou Technology
BLAgent: Agentic RAG for File-Level Bug Localization
May 18, 2026Md Afif Al Mamun, Gias UddinSoftware Engineering Agents LLM Reranking
University of Calgary, Canada · York University, Canada
AMATA: Adaptive Multi-Agent Trajectory Alignment for Knowledge-Intensive Question Answering
May 17, 2026Taolin Zhang, Dongyang Li, Chen Chen +5Direct Preference Optimization Agentic RAG
School of Computer Science and Information Engineering, Hefei University of Technology · Shanghai University of Electric Power · Guangdong University of Finance and Economics +2
SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning
May 16, 2026Yongfeng Huang, Ruiying Chen, James ChengRetrieval-Augmented Generation Healthcare
CSE, The Chinese University of Hong Kong · Wuhan University of Technology
RAGA: Reading-And-Graph-building-Agent for Autonomous Knowledge Graph Construction and Retrieval-Augmented Generation
May 16, 2026Chengrui Han, Zesheng ChengKG Construction Graph Retrieval-Augmented Generation
Qingdao University
GRASP: Graph Agentic Search over Propositions for Multi-hop Question Answering
May 15, 2026Stockton Jenkins, Ramya Korlakai Vinayak, Junjie HuMulti-Hop QA Graph Retrieval-Augmented Generation
University of Wisconsin-Madison
Scaling Retrieval-Augmented Reasoning with Parallel Search and Explicit Merging
May 13, 2026Jiabei Liu, Wenyu Mao, Junfei Tan +4Multi-Hop QA Agentic RAG
University of Science and Technology of China · WeChat Technical Architecture Department, Tecent Inc.
Goal-Oriented Reasoning for RAG-based Memory in Conversational Agentic LLM Systems
May 12, 2026Jiazhou Liang, Armin Toroghi, Yifan Simon Liu +3Multi-Hop QA Agentic RAG
University of Toronto · Vector Institute for Artificial Intelligence
CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG
May 12, 2026Jianghan Shen, Siqi Luo, Xinyu Cheng +6RL for Language Models Reinforcement Learning
1Nanjing University · 2Shanghai Artificial Intelligence Laboratory · University of Hong Kong +1
NyayaAI: An AI-Powered Legal Assistant Using Multi-Agent Architecture and Retrieval-Augmented Generation
May 11, 2026Deepanshu, Divi Saxena, Deepali Rana +2Multi-Agent LLM Systems Legal IR
School of Computer Science UPES, Dehradun, India
Bridging Modalities, Spanning Time: Structured Memory for Ultra-Long Agentic Video Reasoning
May 8, 2026Jiazheng Li, Chi-Hao Wu, Yunze Liu +3Video Understanding Multimodal Memory
University of Connecticut · Northwestern University · University of Virginia
RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
May 8, 2026Shijun Li, Pranav Belligundu, Tianxin Wei +3Agentic RAG Recommender Systems
The University of Texas at Austin · University of Illinois at Chicago · Capital One AI Foundations +1

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Cascading Hallucination in Agentic RAG: The CHARM Framework for Detection and Mitigation

Saroj Mishra

University of North Dakota

LLM Hallucination Mitigation Hallucination in Language Models Agentic RAG LLM Hallucination Detection LLM Agent Reliability

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Multi-step agentic retrieval-augmented generation (RAG) pipelines have demonstrated significant capability for complex reasoning tasks, yet remain vulnerable to a class of failure that existing hallucination detection mechanisms systematically miss: cascading hallucination, where errors introduced at early pipeline stages propagate and amplify across successive reasoning steps, producing confident but factually incorrect final outputs. To address this vulnerability, we formalize cascading hallucination as a distinct failure mode in agentic RAG systems, present a four-type taxonomy of cascade patterns, and introduce CHARM (Cascading Hallucination Aware Resolution and Mitigation), an architectural framework for detecting and interrupting error propagation in multi-step reasoning pipelines. CHARM comprises four components - stage-level fact verification, cross-stage consistency tracking, confidence propagation monitoring, and cascade resolution triggering - that operate alongside standard agentic RAG pipelines without requiring architectural replacement. We evaluate CHARM on HotpotQA, MuSiQue, 2WikiMultiHopQA, and a custom adversarial dataset across LangChain agentic pipeline configurations, achieving an 89.4% cascade detection rate with a 5.3% false positive rate and 215 ms +/- 18 ms average latency overhead per stage, achieving an error propagation reduction of 82.1%, compared to 18.5% for output-level detectors. Component ablations confirm that each detection module contributes meaningfully to overall cascade coverage. CHARM integrates with human-in-the-loop oversight frameworks to provide a complete reliability and governance stack for production agentic AI deployment.

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Latest papers 153