Hypergraph-Based RAG

RAG: Retrieval-Augmented Generation

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9 papers1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

STITCH-RAG: Spatio-Temporal Influence Tracing over Topic Hypergraphs for Multi-Hop Retrieval-Augmented Generation
Sep 28, 2026Haodong Yang, Mengzhu Chen, Jia CaiMulti-Hop QA Retrieval-Augmented Generation
School of Statistics And Data Science, Guangdong University of Finance & Economics Guangzhou, China
PRISM-RAG: Multimodal Hypergraph Retrieval-Augmented Generation for Tobacco Product and Legislative Policy Reasoning
Sep 20, 2026Manuel Serna-Aguilera, Raegan Anderes, Page Dobbs +1Multimodal RAG Legal IR
Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, 72205
HyperProve: Answer-Guided Hypergraph Expansion for Multi-Hop Question Answering
Sep 12, 2026An Nguyen Phu, Dung Nguyen Quang, Luu Hieu An +3Multi-Hop QA Factual QA
Hanoi University of Science and Technology · Monash University · University of Oregon
VizRAG: Enhancing Retrieval-Augmented Generation with Hypergraph Visualization
Jul 22, 2026Yanbin Wei, Yang Chen, Renling Gan +7Multimodal RAG Retrieval-Augmented Generation
1Southern University of Science and Technology · 2Hong Kong University of Science and Technology · 3Huawei Research +1
Trace Only What You Need: Structure-Aware On-Demand Hypergraph Memory for Long-Document Question Answering
Jun 9, 2026Xiangjun Zai, Xingyu Tan, Chen Chen +2Retrieval-Augmented Generation Graph Retrieval-Augmented Generation
University of New South Wales, Australia · CSIRO, Australia · University of Wollongong, Australia
Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models
Apr 14, 2026Keshu Wu, Chenchen Kuai, Zihao Li +6Hypergraph-Based RAG Retrieval-Augmented Generation
Texas A&M University · University of Illinois Urbana-Champaign · The University of Kansas
MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers
Apr 5, 2026Zhihan Guo, Yuting Lu, Jionghao LinRetrieval-Augmented Generation Knowledge Augmentation for Language Models
The University of Hong Kong, Hong Kong SAR, China · Carnegie Mellon University, Pittsburgh PA 15213, USA · Monash University, Clayton VIC 3800, Australia
NICO-RAG: Multimodal Hypergraph Retrieval-Augmented Generation for Understanding the Nicotine Public Health Crisis
Mar 2, 2026Manuel Serna-Aguilera, Raegan Anderes, Page Dobbs +1Hypergraph-Based RAG Multimodal RAG
University of Arkansas, Fayetteville, AR, 72701, USA · University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA
HyperRAG: Reasoning N-ary Facts over Hypergraphs for Retrieval Augmented Generation
Feb 16, 2026Wen-Sheng Lien, Yu-Kai Chan, Hao-Lung Hsiao +5Hypergraph-Based RAG Retrieval-Augmented Generation
National Yang Ming Chiao Tung University, Hsinchu, Taiwan · E.SUN Bank, Taipei, Taiwan · National Kaohsiung Normal University, Kaohsiung, Taiwan

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STITCH-RAG: Spatio-Temporal Influence Tracing over Topic Hypergraphs for Multi-Hop Retrieval-Augmented Generation

Haodong Yang, Mengzhu Chen, Jia Cai

School of Statistics And Data Science, Guangdong University of Finance & Economics Guangzhou, China

Multi-Hop QA Retrieval-Augmented Generation Graph Retrieval-Augmented Generation Graph-Based Retrieval Hypergraph-Based RAG

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Multi-hop retrieval-augmented generation requires a retriever to connect evidence distributed across documents while preserving a concise, faithful generation context. Existing indexes leave two complementary gaps: chunk-based RAG can break cross-passage evidence chains, whereas an unlabeled pairwise projection without generating-topic provenance cannot jointly preserve topic-level co-participation and per-occurrence entity descriptions. We propose STITCH-RAG, a hypergraph-based framework with three coupled components. First, a semi-merged topic hypergraph encodes multi-entity co-participation as topic-summary hyperedges while retaining per-chunk entity states linked by canonical-name equivalence. Second, spatio-temporal influence bridging propagation (STIBP) combines topic-space propagation with deterministic chunk-index linkage across name-equivalent states under frequency-adaptive decay. Third, continuous STIBP scores replace binary entity-match seeds in localized Personalized PageRank (PPR). We characterize the condition under which this prior assigns more PPR mass to ground-truth evidence than a binary prior. Under the reported protocol, STITCH-RAG attains the highest reported Contain-Acc and LLM-Acc point estimates among the compared methods on HotpotQA and 2WikiMultiHopQA, and higher Recall@8 than the methods included in the standardized retrieval comparison. Results on the mixed-domain benchmark remain auxiliary preference-based evidence because only LLM-judged accuracy is available.