[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-aria-turns-math-conjectures-into-lean-proofs-more-reliably":10,"sections":34},{"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":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},3561,"aria-turns-math-conjectures-into-lean-proofs-more-reliably","Aria Turns Math Conjectures Into Lean Proofs More Reliably","A new agent called Aria uses a dependency graph approach to formalize research-level math in Lean, outperforming prior methods on several benchmarks.","An AI agent called Aria can now translate high-level mathematical conjectures into verified Lean code at accuracy rates that leave previous methods behind.\n\nAria works in two phases. First, it breaks a conjecture into a dependency graph — a recursive map of every concept the statement relies on. Then it builds the formal Lean code bottom-up from those grounded pieces. A companion module called AriaScorer checks each term against Mathlib, Lean's standard math library, to catch semantic mismatches before they propagate. On the ProofNet benchmark, Aria hit a 91.6% compilation success rate and 68.5% final accuracy. On FATE-X, a set of hard algebra problems drawn from research literature, it scored 44.0% versus 24.0% for the best prior baseline. On a dataset of homological conjectures, Aria reached 42.9% accuracy while every other tested model scored zero.\n\nAuto-formalization matters because verified proofs are the gold standard for mathematical certainty — and writing Lean by hand is slow even for experts. If a system can reliably translate a conjecture stated in plain math into machine-checkable code, it shortens the path from \"we think this is true\" to \"we can prove this is true.\" The homological conjecture result is the most striking: reaching nearly 43% on problems where rivals scored nothing suggests the dependency-graph approach handles structural complexity that flat LLM generation cannot.\n\nThe caveat worth noting: benchmark accuracy and real-world research utility are different things. A 68.5% final accuracy on ProofNet means roughly one in three attempts still fails, and research conjectures are often messier than curated benchmarks — so treat the numbers as a promising signal, not a finished tool.","[\"ai\",\"math\",\"formal-verification\",\"lean\"]","2026-07-03T04:00:00.000Z","2026-07-03T08:40:11.943Z","2026-07-03T08:40:14.872Z","published",null,[],"ai",[24,26,27,28],"math","formal-verification","lean",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2510.04520",0,{"sections":35},[36,40,45,50,55,60,65,70,75,80,85,89,94,99],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":71,"slug":72,"count":73,"latest_published_at":74},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":76,"slug":77,"count":78,"latest_published_at":79},"Dev Tools","dev-tools",59,"2026-07-07T04:00:00.000Z",{"name":81,"slug":82,"count":83,"latest_published_at":84},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":86,"slug":87,"count":83,"latest_published_at":88},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":90,"slug":91,"count":92,"latest_published_at":93},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":95,"slug":96,"count":97,"latest_published_at":98},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":100,"slug":101,"count":102,"latest_published_at":103},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]