Retrieval-Augmented Reasoning

Latest papers

47 papers16 papers in the last four weeks, up 433% on the four weeks before. 0.1% of all new papers.

AgenticRAG: Agentic Retrieval for Enterprise Knowledge Bases
May 7, 2026Susheel Suresh, Hazel Mak, Shangpo Chou +2Tool-Augmented Language Model Agents Agentic Search
Microsoft Corporation
RAG over Thinking Traces Can Improve Reasoning Tasks
May 5, 2026Negar Arabzadeh, Wenjie Ma, Sewon Min +1Retrieval-Augmented Generation Retrieval-Augmented Reasoning
University of California, Berkeley
When to Retrieve During Reasoning: Adaptive Retrieval for Large Reasoning Models
Apr 29, 2026Dongxin Guo, Jikun Wu, Siu Ming YiuRetrieval-Augmented Generation Retrieval-Augmented Reasoning
The University of Hong Kong Hong Kong, China · Brain Investing Limited Hong Kong, China · Stellaris AI Limited Hong Kong, China
OASIS: On-Demand Hierarchical Event Memory for Streaming Video Reasoning
Apr 18, 2026Zhijia Liang, Jiaming Li, Weikai Chen +3Streaming Video Understanding Retrieval-Augmented Reasoning
Sun Yat-sen University · OPPO AI Center · Shenzhen Loop Area Institute +1
Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning
Apr 13, 2026Bo Li, Mingda Wang, Gexiang Fang +2Retrieval-Augmented Generation Adaptive RAG
National Engineering Research Center for Software Engineering, Peking University · School of Computer Science, Peking University · School of Health Sciences and Biomedical Engineering, Hebei University of Technology
When Meaning Isn't Literal: Exploring Idiomatic Meaning Across Languages and Modalities
Apr 12, 2026Sarmistha Das, Shreyas Guha, Suvrayan Bandyopadhyay +3Retrieval-Augmented Reasoning Figurative Language Understanding
Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, India · School of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand
RecaLLM: Addressing the Lost-in-Thought Phenomenon with Explicit In-Context Retrieval
Apr 10, 2026Kyle Whitecross, Negin RahimiRetrieval-Augmented Reasoning Long-Context Reasoning in Language Models
University of Massachusetts Amherst
Beyond the Parameters: A Technical Survey of Contextual Enrichment in Large Language Models: From In-Context Prompting to Causal Retrieval-Augmented Generation
Apr 3, 2026Prakhar Bansal, Shivangi AgarwalKnowledge Augmentation for Language Models Retrieval-Augmented Generation
Procedural Knowledge at Scale Improves Reasoning
Apr 1, 2026Di Wu, Devendra Singh Sachan, Wen-tau Yih +1Retrieval-Augmented Reasoning LLM Reasoning
University of California, Los Angeles · Meta FAIR
PAR $^2$ -RAG: Planned Active Retrieval and Reasoning for Multi-Hop Question Answering
Mar 30, 2026Xingyu Li, Rongguang Wang, Yuying Wang +5Multi-Hop RAG Retrieval-Augmented Generation
Oracle AI
GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem Structuring
Mar 26, 2026Xinyi Duan, Yuanrong Tang, Jiangtao GongRetrieval-Augmented Reasoning Retrieval-Augmented Generation
Tsinghua University
Evaluate-as-Action: Self-Evaluated Process Rewards for Retrieval-Augmented Agents
Mar 10, 2026Jiangming Shu, Yuxiang Zhang, Ye Ma +2Retrieval-Augmented Reasoning Agentic RAG
School of Computer Science and Technology, Beijing Jiaotong University · Hithink Research
StratRAG: A Multi-Hop Retrieval Evaluation Dataset for Retrieval-Augmented Generation Systems
Mar 6, 2026Aryan PatodiyaMulti-Hop Retrieval RAG Evaluation
Department of Computer Science, California State University, Fresno, Fresno, CA, USA
AutoPrunedRetriever: Persistent Reasoning Graphs for Efficient and Extensible Retrieval-Augmented Generation
Feb 4, 2026Ning Wang, Kuanyan Zhu, Daniel Yuehwoon Yee +4RAG Context Compression Retrieval-Augmented Generation
Cornell University · University of Cambridge · The University of Hong Kong +2
Mindscape-Aware Retrieval Augmented Generation for Improved Long Context Understanding
Dec 19, 2025Yuqing Li, Jiangnan Li, Zheng Lin +4Retrieval-Augmented Generation Long-Context Reasoning in Language Models
Institute of Information Engineering, Chinese Academy of Sciences · School of Cyber Security, University of Chinese Academy of Sciences · WeChat AI, Tencent +1
REAP: Enhancing RAG with Recursive Evaluation and Adaptive Planning for Multi-Hop Question Answering
Nov 13, 2025Yijie Zhu, Haojie Zhou, Wanting Hong +2Multi-Hop QA Retrieval-Augmented Reasoning
The School of Artificial Intelligence and Computer Science, Jiangnan University
Retrieval as Exploration: Retriever-Free Retrieval via Corpus-Traversing MCTS
May 22, 2025Chaeeun Kim, Seungone KimKnowledge Retrieval in Language Models Retrieval-Augmented Reasoning
LBOX · Carnegie Mellon University

May 7, 2026J/K move · Enter open · S save

AgenticRAG: Agentic Retrieval for Enterprise Knowledge Bases

Susheel Suresh, Hazel Mak, Shangpo Chou, Fred Kroon+1

Microsoft Corporation

Tool-Augmented Language Model Agents Agentic Search LLM Agent Harnesses Knowledge-Intensive QA Agentic Retrieval Agentic RAG+4

Open paper AskPDF arXiv

We present AgenticRAG, a practical agentic harness for retrieval and analysis over enterprise knowledge bases. Standard RAG pipelines place significant burden of grounding on the search stack, constraining the language model to a fixed candidate set chosen deep in the retrieval process. Our approach reduces this overdependence by layering a lightweight harness on top of existing enterprise search infrastructure, equipping a reasoning LLM with search, find, open, and summarize tools enabling the model to iteratively retrieve information, navigate within documents, and analyze evidence autonomously. On three open benchmarks we observe substantial gains:

49.6\%

recall@1 on BRIGHT (+21.8 pp over the best embedding baseline), 0.96 factuality on WixQA (

+13\%

relative improvement), and

92\%

answer correctness on FinanceBench--within 2 pp of oracle access to true evidence. Ablation studies show that the most significant factor is the shift from single-shot retrieval to agentic tool use (

5.9\times

improvement), while multi-query search and in-document navigation contribute to both quality and efficiency. We present various design choices in our agentic harness that were informed by pre-production deployments. Our results demonstrate its suitability for real-world enterprise production environments.