LLM Answer Verification

LLM: Large Language Model

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What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification
Sep 29, 2026Adrian de WynterLLM Answer Verification Dynamic Epistemic Logic
Microsoft and the University of York
Halluscoring 2026: The first shared task on llms hallucination detection and answer verification
Sep 29, 2026Aisha Alansari, Abdessalam Bouchekif, Ahmed Hasanaath +9LLM Evaluation LLM Answer Verification
King Fahd University of Petroleum and Minerals, Saudi Arabia · Hamad Bin Khalifa University, Qatar · University of the Basque Country, Spain +5
Locating Answer-Correctness Signals in Frozen Large Language Models
Sep 29, 2026Yuansen Liu, Yixuan Tang, Anthony Kum Hoe TungLLM Answer Verification Language Model Error Detection
School of Computing, National University of Singapore
Test-Time Scaling via Budgeted Multi-Attribute Verification
Sep 28, 2026Bo Xue, Ji Cheng, Shen-Huan Lyu +2Multi-Armed Bandits LLM Answer Verification
City University of Hong Kong · Hohai University · Zhejiang University
Knowing Is Not Choosing: What Explicit Verification Adds Beyond Generative Preference
Sep 27, 2026Yilong Li, Chengpo Yan, Aayan Arish +1LLM Evaluation LLM Answer Verification
Department of Computer Science University of Wisconsin-Madison Madison, WI 53703, USA
Return or Revise? Learning When Revision Helps Retrieval-Augmented QA
Sep 24, 2026Nicholas Kashani Motlagh, Tim Anderson, Jeremy Gwinnup +1Retrieval-Augmented Generation LLM Answer Verification
DCS Corp · Air Force Research Laboratory
Cross-Lingual Legal QA for Vietnamese Labour Law: Retrieval, Translation, and Verifier-Guided Correction
Sep 23, 2026Nguyen Minh Chi, Mo El-Haj, Nguyen Ha Thanh +2LLM Answer Verification Legal Citation Verification
VinUniversity, Vietnam · Lancaster University, UK · Cardiff University, UK
Human-LLM Deliberation as Interactive Proof: Conditions for Verifiability Without Transparency
Sep 21, 2026Baotong Zhang, Dean Foster, João SedocLLM Answer Verification Anytime-Valid Inference
Stern School of Business New York University New York, NY, USA · Amazon New York, NY, USA
From Tables to Quantified Statements: Evaluating LLM Inference Generation through Executable Verification
Sep 21, 2026Mai Mohamed Eida, Gunjan Anand, Ayush Singh +1Table QA LLM Evaluation
University of Illinois Urbana Champaign
LLM-as-an-Improver: Turning Verification into Better Candidates
Sep 17, 2026Akiyoshi Tomihari, Yuma IchikawaLLM Answer Verification LLM Reranking
Fujitsu Limited Department of Computer Science The University of Tokyo · Fujitsu Limited RIKEN center for AIP
EviGen: Predictive Evidence Scaffolding for Verifiable Clinical Rationale Generation
Sep 16, 2026Fengnan Li, Heman Burre, Liwen Sun +2LLM Answer Verification Clinical Outcome Prediction
Duke University
Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering
Sep 14, 2026Jiashuo Zhang, Yuling Chen, Yvonne Commodore-Mensah +1LLM Grounding LLM Answer Verification
Department of Computer Science Johns Hopkins University · School of Nursing Johns Hopkins University
A decision-basis contract for auditable LLM-assisted medical billing verification: deterministic rules, verbatim evidence, and fail-closed abstention
Sep 14, 2026Jan Hölter, Kevin Geis, Benjamin Raab +1LLM Answer Verification LLM Auditing
Competence Center Artificial Intelligence, Aschaffenburg University of Applied Sciences, Würzburger Straße 45, Aschaffenburg, 63743, Bavaria, Germany.
Can LLMs in Draft-Verify-Revise Pipelines Resolve Deictic Ambiguity?
Sep 14, 2026Obinna I. EkekezieCoreference Resolution LLM Answer Verification
Cambridge Health Alliance, Cambridge, MA, United States of America. · Harvard Medical School, Boston, MA, United States of America.
MedSNIP: Building and Benchmarking Snippet-Level Granularity for Medical Fact Verification
Sep 14, 2026Hasan Iqbal, Sarfraz Ahmad, Hyunjae Kim +5LLM Answer Verification Automated Fact-Checking
Mohamed bin Zayed University of Artificial Intelligence · Yale University · Korea University +2
NovGauge: A Fine-Grained Benchmark for Diagnosing LLMs' Capability in Paper Novelty Assessment
Sep 12, 2026Guoqiang Zhang, Kexin Tan, Ming Zhang +12LLM Evaluation LLM Answer Verification
College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China · Graduate School of Engineering, The University of Tokyo, Tokyo, Japan · AtomInnoLab 4Atom Infinite Pte. Ltd., Singapore +1
GANDR: Claim Auditing for Verifiable Legal Answer Generation
Sep 9, 2026Chen Qian, Yimeng Wang, Yu Chen +2LLM Answer Verification Legal Citation Verification
William & Mary · Anytime AI
How Correct Is Your Answer? A Semantic Correctness Framework for Open QA Evaluation
Sep 1, 2026Elitsa Yotkova, Violeta Kastreva, Petar Velkov +4LLM Answer Verification Language Model Generation Evaluation
Sofia University “St. Kliment Ohridski” · ETH Zürich · University of Zurich +1
Where the Verifier Fails: A Category-Level Audit of Reward Signals in RLVR
Sep 1, 2026Esther XinLLM Answer Verification Reinforcement Learning with Verifiable Rewards
Independent Researcher
Cheap Verifiers, Large Blind Spots: Measuring the Reliability Cost of Cost-Saving Cascades
Sep 1, 2026Dushyant RajputLLM Inference Efficiency LLM Answer Verification
AltSlate Labs LLP
The Answer Is Not the Argument
Aug 31, 2026Will Yeadon, Sergio Juárez, Paul Mackay +5LLM Answer Verification CoT Monitoring
Department of Physics, Durham University, Durham DH1 3LE, UK · Escuela de Ingenier´ıa de Telecomunicaci´on, Department of Signal Theory and Communications, University of Vigo, Vigo E-36310, Spain · Independent Researcher
HSRM: Hidden-State Reward Models for Test-Time Verification
Aug 31, 2026Xianzhi Li, Xiaodan ZhuLLM Answer Verification Efficient Language Model Reasoning
Department of Electrical and Computer Engineering & Ingenuity Labs Research Institute Queen’s University
CLAIR-Fin: An Adversarial Multi-Agent Framework for Claim-Level Verification and Adaptive Debate in Cross-Modal Financial QA
Aug 13, 2026Fatema Tuj Johora Faria, Mukaffi Bin Moin, Jubayer Al Mahmud +2LLM Answer Verification LLM Hallucination Mitigation
Ahsanullah University of Science and Technology, Bangladesh · Jashore University of Science and Technology, Bangladesh · American International University - Bangladesh
Rethinking LLM Verification: Evidence Structure, Uncertainty, and Selective Refinement
Aug 11, 2026Uma Ranjan, Kunal Tilaganji, Aditya Koul +9LLM Grounding LLM Answer Verification
Indian Institute of Technology Jammu · Microsoft Research · SCB Dental College and Hospital, Cuttack
Business Truth, not SQL Accuracy: A Rule-Gated 7B Analytics Agent Outperforms a Direct-Prompted 32B Baseline
Aug 10, 2026Morris LeeLLM Answer Verification LLM Agent Evaluation
Independent Researcher
SymDiag: Explainable Diagnosis for LLM Reasoning via Neuro-Symbolic Verification
Aug 9, 2026Wenyao Cui, Huaping Zhang, Yongyi Huang +6CoT Faithfulness LLM Answer Verification
Beijing Institute of Technology Beijing, China · Zhongguancun Academy Beijing, China · Xinjiang Future Enterprise Incubator Co., Ltd. Xinjiang, China +1
From token probabilities to calibrated confidence: An empirical study of mathematical question answering
Aug 8, 2026Avery Ma, Lorne Schell, Vin Bhaskara +1LLM Answer Verification Confidence Estimation in Language Models
RBC Borealis
Don't `Well, Actually' Me Unless You Know What You're Talking About: Weak Presupposition Verification Degrades General QA Performance
Aug 6, 2026Shenran Wang, Vered Shwartz, Hila GonenLLM Evaluation LLM Answer Verification
Department of Computer Science, University of British Columbia · Vector Institute · CIFAR AI Chair +1
RepoProbe: Benchmarking Architecture-Aware Repository Comprehension with Checklists
Aug 5, 2026Yuexi Yang, Alyssa Wu, Ji Luo +4Software Engineering LLM Evaluation
Zhejiang University · Hunyuan, Tencent · Ningbo Global Innovation Center, Zhejiang University
TriQua: Reconciling Granularity and Context in Factuality Evaluation
Aug 5, 2026Jin Liu, Steffen Thoma, Achim RettingerLLM Answer Verification Factual Consistency Evaluation
FZI Research Center for Information Technology, Karlsruhe, Germany · Karlsruhe Institute of Technology, Karlsruhe, Germany · Trier University, Trier, Germany

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What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification

Adrian de Wynter

Microsoft and the University of York

LLM Answer Verification Dynamic Epistemic Logic LLM Reasoning

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We introduce Type-6 logic, a variant of dynamic epistemic logic augmented with two operators (uncertainty and recurrence), designed to model the inferential dynamics of contemporary large language model (LLM) chain-of-thought (CoT) reasoning. Type-6 accounts for common LLM reasoning pathologies such as unlicensed revision, enthymemes, loopbacks, and unverifiable/incorrect claims. We propose a verifier based on Type-6 logic that builds a graph out the trace, and checks it against Type-6's axioms and inference rules. We evaluate our framework on LLM-generated CoTs four splits spanning formal and informal reasoning. Our verifier detects structurally unsound reasoning steps that surface-level heuristics miss, and allows for easy visualisation of the model's reasoning process. In our corpus, our verifier shows that derived contradiction is the most common hard-fail category in CoT, and that only about 3% of the propositions of a trace have impact on the final derivation. Ablation studies show that other verification methods (LLMs-as-judges, other neurosymbolic approaches, etc.) cannot be considered interchangeable: for example, agreement between LLMs-as-judges and LINC is

κ\approx 0.034

, and this persists within a method across underlying models. Type-6, however, is the most agreed-with method amongst the ones we tested. We prove our verifier runs on average-case linear time; and release our logic specification and artefacts.

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