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arXiv AI

Verification abundance, adjudication scarcity: what happens to mathematical knowledge when proof checking becomes free

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arXiv Computation and Language
1d ago

SoK: Formal Methods for Fact-Checking and Information Integrity

The paper "SoK: Formal Methods for Fact-Checking and Information Integrity" discusses how automated fact‑checking systems typically output a verdict but lack a detailed record—called a warrant—explaining the evidence and conditions behind that verdict. It proposes organizing the field by what is being formalised—claims, reasoning, checking systems, ecosystems, and regulatory obligations—rather than by pipeline stages, and surveys 121 works to identify gaps, notably the scarcity of formal methods applied to verifying the checking systems themselves. The authors highlight that existing formal tools, though largely unused in this domain, could address these gaps and outline open problems with suggested first steps.

By Nikolaos Kekatos, Theodoros Nestoridis, Charalampos Bratsas, Charalampos Dimoulas, Georgios Konstantinidis, Georgios Malogiannis, Michael Sirivianos, Andreas Veglis
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arXiv Computer Vision
Sep 4

VeriPhy: Agentic Physical Reasoning for World Model Evaluation and Refinement

VeriPhy is an auditable physical‑verification system that transforms a text prompt into typed physical obligations and a statically validated execution plan before any video frames are generated. During execution, it gates calls to frozen low‑level experts (segmentation, tracking, counting, depth, OCR, audio‑event detection, etc.) and records provenance‑carrying evidence for each action. The system maps these records to a three‑valued state—supported, contradicted, or unknown—providing traceable verdicts that can be used to refine generation models.

By Wenzhuo Xu, Yuchen Zhu, Chongjian Ge, Xuan Shen, Jing Shi, Jason Kuen, Yongxin Chen, Molei Tao, Christopher McComb, Noelia Grande Guti\'errez, Jiuxiang Gu
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arXiv Computation and Language
1d ago

Euston: Training Away Mathematical Sycophancy Without Losing the Mathematics

Euston is an 8‑B parameter mathematical claim‑verification model that resists producing false derivations when presented with corrupted theorems. It was trained on 3,026 matched true/corrupted statement pairs generated by GraphSynth, a probabilistic factor‑graph generator, and fine‑tuned from DeepSeek‑R1‑8B using GRPO. On a balanced held‑out split, Euston’s balanced accuracy rose from 29.50 % to 63.75 %, and its discrimination gap improved from –0.5 % to +27.5 %, while maintaining comparable general mathematical ability and reducing response length and truncation rates.

By Zehua Cheng, Wei Dai, Jiahao Sun
llmsfine-tuningsafety
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arXiv AI
Sep 3

ClaimReceipt: Verifying Evidence Sufficiency and Coverage in Agent Evaluations

The paper introduces ClaimReceipt, a specification and verifier that checks whether a claim in an agent evaluation can be recomputed from retained evidence (sufficiency) and whether the evidence covers the entire experiment set (coverage). Using the CR‑2 verifier on 1,392 historical records, the authors demonstrate accurate reproduction of audit verdicts, non‑redundant field groups, and zero false positives on semantic faults. In a prospective CR‑3 run, the system correctly flags missing receipts and preserves coverage when private evidence is withheld, while adding minimal overhead to inference time and transaction size.

By Peiying Zhu, Sidi Chang
agents
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