[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-mask-proof-pipeline-offers-automatic-step-level-math-proof-evaluation":10},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":22,"tags":24,"sources":28,"feedback":32,"feedback_at":22,"cost_usd":32,"total_tokens":32},1233,"mask-proof-pipeline-offers-automatic-step-level-math-proof-evaluation","Mask-Proof pipeline offers automatic step-level math proof evaluation","Researchers release Mask-ProofBench, a curated set of 292 masked-proof tasks that let LLMs be judged on intermediate reasoning with near‑expert accuracy.","Mask-Proof turns existing mathematical proofs into masked-step questions that an LLM must fill in.\n\nThe authors took real research proofs, hid critical formula steps, and kept surrounding context. An LLM‑based equivalence judge scored each reconstruction, using repeated votes for stability. The resulting benchmark – Mask-ProofBench – contains 292 problems from a range of fields. Tests on 17 language models showed reasoning‑enhanced variants beat standard versions by 12‑27%, while the judge matched expert annotators 96.8% of the time.\n\nThis matters because most current math‑oriented benchmarks focus on final answers or require costly human grading. By checking intermediate steps automatically, researchers can compare models on proof‑level reasoning at scale. The high agreement with experts also means the metric is trustworthy enough for iterative model development.\n\nIf the community adopts this approach, we may see faster progress on AI‑assisted theorem proving, but the pipeline still depends on a handcrafted masking stage and a single judge model, so broader validation will be needed.","[\"ai\",\"math\",\"benchmarks\"]","2026-06-16T04:00:00.000Z","2026-06-16T19:56:39.884Z","2026-06-16T19:56:42.780Z","published",null,[],[25,26,27],"ai","math","benchmarks",[29],{"name":30,"url":31},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.15258",0]