Evidence Selection

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5 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Latest papers 35

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MiniVer-V: Identifying Minimal Sufficient Evidence for Short Video Verification
Oct 8, 2026Leran Chen, Lingnan Kong, Zile CaiClaim Verification Automated Fact-Checking
The University of Sydney
Has LLM Screening Performance Stalled in Software Engineering Systematic Reviews?
Oct 7, 2026Aleksi Huotala, Miikka Kuutila, Mika MäntyläEvidence Selection LLM Evaluation
University of Helsinki, Helsinki, Finland. · LUT University, Lahti, Finland.
BELIEFRAG: Making Adaptive RAG State-Aware under Evolving Evidence
Sep 30, 2026Hongji PuAdaptive RAG Evidence Selection
University of Illinois Urbana-Champaign
When to Retrieve, When to Stay: Uncertainty-Aware Temporal Evidence Allocation for Streaming Video-LLMs
Sep 29, 2026Xiang Hu, Jiazuo Yu, Lu Zhang +2Streaming Video Understanding Evidence Selection
IIAU Lab, Dalian University of Technology
What Changes When Fact-Verification Scores Improve? Evidence and Answer Accounting Across Trained Verifiers and LLMs
Sep 22, 2026Han Chen, Yingrui LiLLM Evaluation Evidence Selection
A Benchmark Framework for Screening Automation in Systematic Reviews
Sep 16, 2026Gauransh Kumar, Luciano Marchezan, Guillaume Genois +2LLM Evaluation Evidence Selection
Université de Montréal Montreal, Canada
CITECHOICE: A Causal Audit of How Document Presentation Redistributes Citation Credit in Agentic Search
Sep 14, 2026Sriram Selvam, Anneswa GhoshEvidence Selection Agentic Retrieval
PAGE-RAG: Provenance-Aware Graph Evidence Promotion for Fixed-Budget Multi-hop Retrieval-Augmented Generation
Aug 30, 2026Haokun Deng, Xunkai Li, Hongchao Qin +1Multi-Hop QA Retrieval-Augmented Generation
Department of Computer Science, Beijing Institute of Technology
HNR-DAC: Hard-Negative Reranking and Distribution-Aligned Classification for Scientific Claim Verification
Aug 7, 2026Zhenchao Wang, Xin Chen, Luoxi Zhang +2Claim Verification Distribution Shift
Southern University of Science and Technology, Shenzhen, China · Institute of Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, China · Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
Evidence-Grounded Constraint Checking in Construction Documents
Jul 31, 2026Rashid Mushkani, Hugo Berard, Shin KosekiEvidence-Grounded Reasoning Evidence Selection
Cocoon Lab.
Evaluation design conditions the expert-vs-auto MeSH gap: a controlled comparison of bag-of-words and BiomedBERT on the Cohen benchmark
Jul 23, 2026Samuel M. Okoe-MensahBenchmark Design Evidence Selection
Accra, Ghana
Best-of-Evidence: Best-of-N Selection under Partial Verification
Jul 23, 2026Cenwei Zhang, Teng Fang, Yuxia Wang +3Model Selection Evidence-Grounded Reasoning
IQuest Research · INSAIT · Technical University of Denmark
Reinforcement Learning for Large Language Model Selective Evidence Adoption from Contaminated Retrieval Results
Jul 22, 2026Yanyu Chen, Yue Li, Yongyi Cui +2RL for Language Models Retrieval-Augmented Generation
East China Normal University · Shandong University
MIRA-Ev:A Benchmark for Granular Evidence Detection and Relational Reasoning in Clinical Exams
Jul 21, 2026Iker De la Iglesia, Johanna Ramirez-Romero, Jose Maria Villa-Gonzalez +3Multilingual Language Model Evaluation Argument Mining
HiTZ Center, University of the Basque Country (EHU) · Hospital Universitario de Cruces
Evidence Interfaces Shape How Retrieval-Augmented Readers Use Support
Jul 19, 2026Junchi Liao, Jiawen Deng, Fuji RenMulti-Hop QA Learning to Rank
QUBO-Optimized Evidence Selection for Retrieval-Augmented Question Answering with Unconventional Solvers
Jul 14, 2026Rahul Singh, Madhav VadlamaniMulti-Hop QA Retrieval-Augmented Generation
University of California Santa Barbara · Georgia Institute of Technology
STEC: Evidence Compression for Deep Search in Open-domain Multi-Hop QA
Jul 12, 2026Xinkang Li, Rong Jiang, Xin Song +3Multi-Hop QA LLM Answer Verification
National University of Defense Technology, China · Harbin Institute of Technology, Shenzhen, China
Evidence-State Rewards for Long-Context Reasoning
Jul 2, 2026Ya Gao, Pekka MarttinenProcess Reward Models RL for Language Model Reasoning
1Aalto University
The Course of News Events: A Comparison of Bottom-Up and Top-Down Approaches for Collecting Text-Based Data about Disasters
Jul 1, 2026Brielen Madureira, Andreas Niekler, Mariana Madruga de BritoEvidence Selection Computational Social Science
LeipzigLab – Climate Discourse, Leipzig University, Germany · Helmholtz Centre for Environmental Research, Germany · Computational Humanities, Leipzig University, Germany
Charting the Growth of Social-Physical HRI (spHRI): A Systematic Review Pipeline Augmented by Small Language Models
Jun 24, 2026Mayumi Mohan, Ju-Hung Chen, Alexis E. BlockEvidence Selection Small Language Models
Case Western Reserve University Cleveland, USA
Understanding LLMs in Title-Abstract Screening: From Disagreements to Recommendations
Jun 16, 2026Mika Mäntylä, Patricia Matsubara, Katia Romero Felizardo +5LLM Evaluation Evidence Selection
University of Helsinki, Finland · UFMS, Brazil · UTFPR – Federal University of Technology - Paraná, Brazil +3
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
Beyond Topical Similarity: Contrastive Evidence Retrieval with Interpretable Attention Alignment in RAG
May 31, 2026Francielle Vargas, João Robiatti, Diego Alves +6Retrieval-Augmented Generation Evidence Selection
University of Chile · São Paulo State University · Saarland University +4
AuthTrace: Diagnosing Evidence Construction in Thematically Dense Single-Author Corpora
May 25, 2026Xiaoqing Wu, Feifei Li, Haoliang Ming +1Evidence Selection RAG Evaluation
WeChat, Tencent Inc., Beijing, China
ECPO: Evidence-Coupled Policy Optimization for Evidence-Certified Candidate Ranking
May 21, 2026Miaobo Hu, Shuhao Hu, BoKun Wang +5Data Provenance Learning to Rank
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China · School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
Claim-Selective Certification for High-Risk Medical Retrieval-Augmented Generation
May 21, 2026Shao KanClaim Verification Healthcare
Jinglue Technology Development (Nanjing) Co., Ltd.
Learning to Select Source-Traceable Evidence for Language-Model Prediction from Irregular Clinical Time Series
May 19, 2026Kwanhyung Lee, Juhwan Choi, Jongheon Kim +5Irregular Time-Series Modeling Healthcare
Kim Jaechul Graduate School of AI, KAIST · AITRICS
Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation
May 13, 2026Weiqing Luo, Zongye Hu, Xiao Wang +3Multimodal RAG Evidence Selection
♦Arizona State University · ♥Texas A&M University · ♠Morgan Stanley
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
Beyond Accuracy: LLM Variability in Evidence Screening for Software Engineering SLRs
Apr 29, 2026Gilberto Sussumu Hida, Danilo Monteiro Ribeiro, Erika YahataSoftware Engineering LLM Evaluation
AIBL · CESAR School · CMCC +1

Oct 8, 2026, cs.CVJ/K move · Enter open · S save

MiniVer-V: Identifying Minimal Sufficient Evidence for Short Video Verification

Leran Chen, Lingnan Kong, Zile Cai

The University of Sydney

Claim Verification Automated Fact-Checking Evidence Selection Selective Prediction

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A core challenge in short-video fact-checking is identifying which evidence is sufficient to support a verification conclusion. Existing approaches either give the verifier all available evidence, introducing noise, or select evidence by topical relevance, which conflates relatedness with sufficiency. We identify evidential sufficiency as the selection criterion: whether a subset of evidence is adequate to support a confident verdict without redundancy. We introduce MiniVer-V, a benchmark of 195 short videos with three-way verdict annotations (supported, refuted, insufficient) and 5,510 multimodal evidence units spanning visual keyframes, speech transcripts, and web-retrieved external sources. We propose a two-layer verification framework that separates claim-video consistency, assessed from internal evidence, from factual verdict determination, which additionally requires external corroboration. On top of it, a sufficiency-driven greedy search assembles evidence until a sufficiency threshold is met and outputs insufficient when the candidate pool is exhausted, rather than forcing a verdict. With Claude Sonnet 4, the method reaches a Macro-F1 of 0.510 using 4.5 evidence units on average (16% of the full evidence set), statistically indistinguishable from the full-evidence baseline (0.518 with 27.7 units), while significantly improving recognition of insufficient cases over the same search without abstention. The efficiency result replicates with GPT-5.5 and holds only partially with an open-weight Qwen2.5-72B verifier. Ablations show that external evidence is indispensable for factual determination, while internal video evidence grounds the verdict in claim-video consistency. These findings suggest that evidence-efficient verification is achievable, and that explicit abstention is needed when evidence is genuinely inadequate.

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