Multi-Hop QA

QA: Question Answering

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16 papers in the last four weeks, up 45% on the four weeks before. 0.2% of all new papers.

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Latest papers 128

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Retrieval as Reasoning: Self-Evolving Agent-Native Retrieval via LLM-Wiki
May 25, 2026Haoliang Ming, Feifei Li, Xiaoqing Wu +1Multi-Hop QA Retrieval-Augmented Generation
WeChat, Tencent Inc., Beijing, China
StepGap: A Hybrid NLI-LLM Checker for Step-Level Evidence-Gap Detectionin Multi-Hop Question Answering
May 23, 2026Yuelyu Ji, Zhuochun Li, Hui Ji +1Multi-Hop QA LLM Answer Verification
School of Computing and Information, University of Pittsburgh
Decompose-and-Refine: Structured Legal Question Answering with Parametric Retrieval
May 23, 2026Jihyung lee, Hyounghun Kim, Gary LeeMulti-Hop QA Legal IR
Graduate School of Artificial Intelligence, POSTECH, Republic of Korea · Department of Computer Science and Engineering, POSTECH, Republic of Korea
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
ContextRAG: Extraction-Free Hierarchical Graph Construction for Retrieval-Augmented Generation
May 19, 2026Roman Prosvirnin, Sergei Kuznetsov, Seungmin JinMulti-Hop QA Graph Retrieval-Augmented Generation
HSE 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.
PersonalAI 2.0: Enhancing knowledge graph traversal/retrieval with planning mechanism for Personalized LLM Agents
May 13, 2026Mikhail Menschikov, Matvey Iskornev, Alexander Kharitonov +8Multi-Hop QA Graph Retrieval-Augmented Generation
Skoltech, Moscow, Russia · SberAI, Moscow, Russia · Huawei, Moscow, Russia +4
Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation
May 13, 2026Jiashuo Sun, Jimeng Shi, Yixuan Xie +10Multi-Hop QA Retrieval-Augmented Generation
University of Illinois Urbana-Champaign · Hong Kong University of Science and Technology · Texas A&M University +1
MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering
May 12, 2026Rezarta Islamaj, Robert Leaman, Joey Chan +13Multi-Hop QA LLM Evaluation
National Library of Medicine, Division of Intramural Research, Bethesda, MD, US · University of Illinois at Urbana-Champaign, Department of Computer Science, Urbana, IL, US · University of Michigan Medical School, Ann Arbor, Michigan, US
Overview of the MedHopQA track at BioCreative IX: track description, participation and evaluation of systems for multi-hop medical question answering
May 12, 2026Rezarta Islamaj, Joey Chan, Robert Leaman +13Multi-Hop QA Healthcare
National Library of Medicine (NLM), National Institutes of Health (NIH), MD, 20894, Bethesda, USA · University of Illinois at Urbana Champaign · Korea University +7
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
HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities
May 10, 2026Shusaku Egami, Aoi Ohta, Tomoki Tsujimura +5Multi-Hop QA Spatiotemporal Reasoning
National Institute of Advanced Industrial Science and Technology (AIST) Koto-ku, Tokyo, Japan
Omni-DeepSearch: A Benchmark for Audio-Driven Omni-Modal Deep Search
May 9, 2026Tao Yu, yiming ding, Shenghua Chai +16Multi-Hop QA Multimodal IR
CASIA · UCAS · BAAI +2
Knowledge-Graph Paths as Intermediate Supervision for Self-Evolving Search Agents
May 7, 2026Huyu Wu, Jun Liu, Xiaochi Wei +3Multi-Hop QA Reward Shaping
Xiaohongshu Inc., Beijing, China
Inference-Time Budget Control for LLM Search Agents
May 7, 2026Zhengru Fang, Senkang Forest Hu, Zhonghao Chang +6Multi-Hop QA Inference-Time Search
City University of Hong Kong · Tsinghua University · Alibaba Ant Group
Evaluating Advanced Prompting on Gemini Flash for Multi-Hop Biomedical QA
May 5, 2026Ahmed Bajaber, Mohammed AlliheediMulti-Hop QA LLM Evaluation
1Saudi Med AI Lab (SMAIL) 2Prince Sultan University, Riyadh, Saudi Arabia · 2Prince Sultan University, Riyadh, Saudi Arabia · 3Al-Baha University, Al Baha, Saudi Arabia
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
$S^3$ -R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data
May 2, 2026Harsh Goel, Akhil Udathu, Susmija Jabbireddy +2Multi-Hop QA Synthetic Data Generation
The University of Texas at Austin · Work done during an internship at Google DeepMind · Google DeepMind
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.
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
EviMem: Evidence-Gap-Driven Iterative Retrieval for Long-Term Conversational Memory
Apr 30, 2026Yuyang Li, Yime He, Zeyu Zhang +1Multi-Hop QA Persistent Memory for Language Models
The Australian National University · UNSW Sydney
SEARCH-R: Structured Entity-Aware Retrieval with Chain-of-Reasoning Navigator for Multi-hop Question Answering
Apr 27, 2026Yuqing Fu, Yimin Deng, Wanyu Wang +9Multi-Hop QA Question Decomposition
City University of Hong Kong · Xi’an Jiaotong University · Michigan State University +2
S2G-RAG: Structured Sufficiency and Gap Judging for Iterative Retrieval-Augmented QA
Apr 26, 2026Minghan Li, Junjie Zou, Xinxuan Lv +2Multi-Hop QA Retrieval-Augmented Generation
Soochow University, Suzhou, China
StructMem: Structured Memory for Long-Horizon Behavior in LLMs
Apr 23, 2026Buqiang Xu, Yijun Chen, Jizhan Fang +5Multi-Hop QA Temporal Reasoning
Zhejiang University · Zhejiang University - Ant Group Joint Laboratory of Knowledge Graph · Ant Group
Query-Aware Flow Diffusion for Graph-Based RAG with Retrieval Guarantees
Apr 21, 2026Zhuoping Zhou, Davoud Ataee Tarzanagh, Sima Didari +7Multi-Hop QA Graph Retrieval-Augmented Generation
Samsung SDS Research America, Mountain View, CA, USA
Evaluating Multi-Hop Reasoning in RAG Systems: A Comparison of LLM-Based Retriever Evaluation Strategies
Apr 20, 2026Lorenz Brehme, Thomas Ströhle, Ruth BreuMulti-Hop QA LLM-as-a-Judge
Universität Innsbruck, Technikerstraße 21a, 6020 Innsbruck, Austria
STRIDE: Strategic Iterative Decision-Making for Retrieval-Augmented Multi-Hop Question Answering
Apr 19, 2026Wei Chen, Lili Zhao, Zhi Zheng +2Multi-Hop QA Self-Training for Language Models
University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence Hefei, Anhui, China · NIO Hefei, Anhui, China
RLM-on-KG: Heuristics First, LLMs When Needed: Adaptive Retrieval Control over Mention Graphs for Scattered Evidence
Apr 18, 2026Andrea Volpini, Elie RaadMulti-Hop QA LLM Reasoning with Graphs
WordLift
IndexRAG: Index-Time Reasoning for Multi-Hop Retrieval-Augmented Generation
Mar 17, 2026Zhenghua Bao, Yi ShiMulti-Hop QA Retrieval-Augmented Generation
Continuum AI Shanghai, China · Continuum AI San Francisco, CA, USA

May 25, 2026, cs.CLJ/K move · Enter open · S save

Retrieval as Reasoning: Self-Evolving Agent-Native Retrieval via LLM-Wiki

Haoliang Ming, Feifei Li, Xiaoqing Wu, Wenhui Que

WeChat, Tencent Inc., Beijing, China

Multi-Hop QA Retrieval-Augmented Generation Tool-Augmented Language Model Agents Agentic Retrieval LLM Agents

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LLM agents require retrieval to behave less like one-shot context fetching and more like reasoning: searching, reading, traversing, and deciding when evidence is sufficient. Yet current Retrieval-Augmented Generation (RAG) systems organize external knowledge as flat chunks retrieved by embedding similarity, exposing a retrieval-as-lookup interface ill-suited to iterative reasoning agents. We propose LLM-Wiki, an agent-native retrieval system that operationalizes the Retrieval-as-Reasoning paradigm by treating external knowledge as a compilable, composable, and self-evolving structure rather than a static retrieval index. LLM-Wiki compiles documents into structured Wiki pages with bidirectional links, exposes search, read, and link-following operations through standard tool-calling interfaces, and introduces an Error Book for persistent structural and semantic self-correction. LLM-Wiki achieves state-of-the-art results on HotpotQA, MuSiQue, and 2WikiMultiHopQA, outperforming HippoRAG 2, LightRAG, and GraphRAG by 2.0-8.1 F1 points. On AuthTrace, LLM-Wiki achieves the best overall accuracy, with especially strong gains on multi-document structured queries, confirming that compilation-based retrieval generalizes beyond chain-style multi-hop reasoning.

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