Hybrid Retrieval

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6 papers in the last four weeks, up 50% on the four weeks before. 0.1% of all new papers.

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Latest papers 57

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HistoRAG: Embedding Historical Methodology in Retrieval-Augmented Generation Through Critical Technical Practice
Jun 16, 2026Noah J. Kim-Baumann, Torsten HiltmannRetrieval-Augmented Generation Temporal IR
Humboldt-Universität zu Berlin
A Unified Framework for Context-Aware and Relation-Aware Graph Retrieval-Augmented Generation
Jun 16, 2026Haoyang Zhong, Yifei Sun, Antong Zhang +3Graph Retrieval-Augmented Generation Hybrid Retrieval
Zhejiang University Hangzhou, China · Nanyang Technological University Singapore, Singapore · Finvolution Group Shang Hai, China
Uncertainty-Aware Hybrid Retrieval for Long-Document RAG
Jun 11, 2026Hoin Jung, Xiaoqian WangRetrieval-Augmented Generation Information Retrieval
Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette, IN 47907
Multi-Field Hybrid Retrieval-Augmented Generation for Maritime Accident Root Cause Analysis
Jun 11, 2026Seongjin Kim, Sungil KimRetrieval-Augmented Generation Hybrid Retrieval
Department of Industrial Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.
Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis
Jun 9, 2026Ruobing Jiang, Dawei Fu, Cheng Jiang +6Scientific QA High-Energy Physics
State Key Laboratory of Nuclear Physics and Technology, Peking University, China
HKVM-RAG: Key-Value-Separated Hypergraph Evidence Organization for Multi-Hop RAG
Jun 5, 2026Mingyu Zhang, Ying MaMulti-Hop QA Graph Retrieval-Augmented Generation
Faculty of Computing, Harbin Institute of Technology, Harbin, China
Less Context, More Accuracy: A Bi-Temporal Memory Engine for LLM Agents Where a Lean Retrieved Context Beats the Full History
Jun 5, 2026Liuyin WangLong-Context QA LLM Agent Memory
Independent Researcher
Sifei at SemEval-2026 Task 8: Hybrid Retrieval and Query Rewriting for Multi-Turn RAG
Jun 5, 2026Sifei Meng, Dmitry IlvovskyCross-Encoder Reranking Retrieval-Augmented Generation
Faculty of Computer Science HSE University
Executable Schema Contracts: From Automatic Ingestion to Multi-Source Retrieval
Jun 3, 2026Padmaja Jonnalagedda, Yuguang Yao, Xiang Gao +2KG Construction Knowledge Representation
Intuit AI Research
Training-Free Lexical-Dense Fusion for Conversational-Memory Retrieval
Jun 2, 2026Christian LysenstøenLate Interaction Retrieval Lexical Retrieval
Inland Norway University of Applied Sciences · Visiting student, University of California, Berkeley
Reason-Then-Retrieve for CoVR-R with Structured Edit Prompts and Dense-Sparse Fusion
Jun 1, 2026DongQing Liu, MengShi Qi, HongWei JiCross-Modal Retrieval Video Reasoning
Beijing University of Posts and Telecommunications
Dual-Route Top-K Retrieval with 1v1 VLM Reranking for the CoVR-R
May 31, 2026Yuyang Sun, Yongliang Wu, Xingyu Zhu +8Multimodal Reranking Cross-Modal Retrieval
Southeast University · National University of Singapore · Independent Researcher +2
GRASP: Plan-Guided Graph Retrieval with Adaptive Fusion and Reranking on Semi-Structured Knowledge Bases
May 28, 2026Yicheng Tao, Yiqun Wang, Xiangchen Song +3Learning to Rank Graph-Based Retrieval
Department of Electrical Engineering and Computer Science, University of Michigan · Department of Computational Medicine and Bioinformatics, University of Michigan
DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark
May 28, 2026Ruofan Hu, Menghui Zhu, Jieming Zhu +8Multimodal IR LLM Reranking
Zhejiang University · Hangzhou, Zhejiang, China · Huawei Technologies Co., Ltd +2
ConvMemory: A Lightweight Learned Memory Reranker, a Negative Attribution Result, and a Research-Preview Conflict Editor
May 27, 2026Taiheng PanCross-Encoder Reranking Learning to Rank
School of Computing and Information Systems University of Melbourne
Developing an Intelligent Job Recommendation System Using Semantic Retrieval and Explainable AI Techniques
May 26, 2026Hussein Al Awad, Khaled Fathi OmarSemantic Search Recommender Systems
∗Master of Web Science, Syrian Virtual University, Damascus, Syria
Simorgh at SemEval-2026 task 7: Region-Aware Hybrid Retrieval for Low-Resource Cultural Reasoning in Multilingual Question Answering
May 26, 2026Hadi Bayrami Asl Tekanlou, Mahdi Bakhtiyarzadeh, Jafar RazmaraRetrieval-Augmented Generation Cross-Lingual Reasoning in Language Models
University of Tabriz, Tabriz, Iran
Query Symbolically or Retrieve Semantically? A Dataset and Method for Semi-Structured Question Answering
May 26, 2026Mateusz Czyżnikiewicz, Ryszard Tuora, Adam Kozakiewicz +6Graph Retrieval-Augmented Generation Question Answering
Samsung AI Warsaw · Samsung AI Cambridge
RAGEAR: Retrieval-Augmented Graph-Enhanced Academic Recommender
May 26, 2026Francesco Granata, Lorenzo Lamazzi, Misael Mongiovì +2Learning to Rank Educational Technology
Department of Mathematics and Computer Science, University of Catania, Italy · Institute for Cognitive Science and Technology, National Research Council, Italy
Beyond Semantic Similarity: A Two-Phase Non-Parametric Retrieval Workflow for Corporate Credit Underwriting
May 20, 2026Linus Ng Junjia, Ezekiel Tee Kongquan, Kelvin Heng +2Financial Services Retrieval-Augmented Generation
OCBC, Singapore · 2Georgia Institute of Technology.
Loom: Hybrid Retrieval-Scoring Outfit Recommendation with Semantic Material Compatibility and Occasion-Aware Embedding Priors
May 11, 2026Anushree BerliaRecommender Systems Hybrid Retrieval
Tatarstan Toponyms: A Bilingual Dataset and Hybrid RAG System for Geospatial Question Answering
May 7, 2026Mullosharaf K. ArabovQuestion Answering Geospatial Reasoning
Department of Data Analysis and Programming Technologies Institute of Computational Mathematics and Information Technologies Kazan (Volga Region) Federal University Kazan, Russia
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
KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation
May 2, 2026Ngoc Luyen Le, Marie-Hélène Abel, Bertrand LaforgeLLM Grounding Hybrid Retrieval
Gamaizer.ia, 93340 Le Raincy, France · Université de technologie de Compiègne, CNRS, Heudiasyc (Heuristics and Diagnosis of Complex Systems), CS 60319 - 60203 Compiègne Cedex, France · Sorbonne Université, CNRS UMR 7585, LPMHE (Laboratoire de Physique Nucléaire et des Hautes Énergies), 75252 Paris cedex 05, France
An End-to-End Ukrainian RAG for Local Deployment. Optimized Hybrid Search and Lightweight Generation
Apr 23, 2026Mykola Trokhymovych, Yana Oliinyk, Nazarii NyzhnykRetrieval-Augmented Generation Hybrid Retrieval
Pompeu Fabra University · Independent Researcher
EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval
Apr 19, 2026Yifan Song, Xingjian Tao, Zhicheng Yang +2Graph Retrieval-Augmented Generation Graph-Based Retrieval
1The Hong Kong University of Science and Technology (Guangzhou) · 2The Hong Kong University of Science and Technology
Sustainable Hybrid Document-Routed Retrieval for Financial RAG: Resolving the Robustness-Precision Trade-off
Mar 26, 2026Zhiyuan Cheng, Longying Lai, Yue LiuRetrieval-Augmented Generation Financial QA
School of Engineering, Stanford University, Stanford, CA, USA · bSimon Business School, University of Rochester, Rochester, NY, USA · cAccounting & Information Systems, Rutgers University, Newark, NJ, USA

Jun 16, 2026, cs.CLJ/K move · Enter open · S save

HistoRAG: Embedding Historical Methodology in Retrieval-Augmented Generation Through Critical Technical Practice

Noah J. Kim-Baumann, Torsten Hiltmann

Humboldt-Universität zu Berlin

Retrieval-Augmented Generation Temporal IR RAG Evaluation Hybrid Retrieval

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Retrieval-Augmented Generation (RAG) is the prevailing architecture for grounding language model outputs in external evidence, yet its dominant evaluation paradigms and default configurations remain oriented toward factual question-answering. For interpretive disciplines such as historical studies, RAG embeds assumptions that conflict with scholarly practice. We introduce HistoRAG, a framework that translates historiographical principles into concrete architectural interventions. Separated retrieval and generation decouples source discovery from interpretation, temporal windowing enforces balanced source representation across the research period as a methodological requirement of historical inquiry, and LLM-as-judge evaluation makes relevance judgments transparent and contestable. We evaluate these interventions using SPIEGELragged, applied to 102,189 articles from Der Spiegel (1950-1979). Each intervention addresses a measurable deficiency in standard RAG: era-specific vocabulary retrieves zero chunks from the 1950s when using 1970s terminology, evidence of the temporal skew that motivates windowing; vector similarity and LLM-assessed relevance correlate only weakly (Spearman rho = 0.275), motivating post-retrieval evaluation; and keyword-based and semantic retrieval surface largely disjoint source pools, motivating an architecture in which both operate as complementary retrieval layers under a shared LLM evaluation filter. We also introduce the concept of Zwischentexte (intermediate texts that function as interpretive proposals rather than findings) as a framework for responsible integration of LLM-generated text into scholarly practice. The architecture offers a model for how domain-specific epistemological commitments can be translated into RAG design decisions, and may transfer to other interpretive disciplines working with large corpora.

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