[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-researchers-separate-evidence-reading-from-verdict-math-in-ai":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},5042,"researchers-separate-evidence-reading-from-verdict-math-in-ai","Researchers Separate Evidence Reading From Verdict Math in AI","A new paper argues combining evidence-reading and vote-tallying in one prompt causes systematic errors, and proposes a fix usable beyond language models.","A new AI research paper says systems that pool evidence from many sources are quietly doing bad math, and it has a fix.\n\nResearchers behind the paper argue that most systems asking a language model to reach a conclusion from many sources dump everything into one prompt. That conflates two different jobs: reading and interpreting a single source (which rewards a big model with lots of context) and combining those interpretations into a verdict (which needs fixed arithmetic and comparable scores across sources). The authors propose separating the two steps with a four-field evidence tuple, made up of a hypothesis, a reliability bucket, a rationale, and provenance, passed between them. They also name a specific failure mode, \"count-scale drift\": thresholding a sum of unweighted scores behaves like probability thresholding, but the threshold quietly shifts depending on how many sources get consulted and how reliable the reader is.\n\nThis is not just a language-model quirk. The authors say the same drift shows up anywhere a system tallies weighted votes, including triage engines, diagnostic panels that count positive results, and other additive multi-signal detectors, and that pooling calibrated log-likelihood ratios rather than summing raw scores avoids it. Tested on a longitudinal medical-style corpus, a small sequence encoder paired with a tree ensemble reached 0.921 AUPRC, against 0.805 for a hand-crafted baseline.\n\nIt is a useful reminder that when a model-based system \"gets it wrong,\" the culprit is often the arithmetic bolted on around the model, not the model's read of any one source.","[\"ai\",\"research\",\"language-models\",\"evidence-aggregation\"]","2026-08-17T04:00:00.000Z","2026-08-17T07:02:21.991Z","2026-08-17T07:02:32.985Z","published",null,[],"ai",[24,26,27,28],"research","language-models","evidence-aggregation",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2608.14509",0,{"sections":35},[36,40,44,49,54,59,64,69,74,79,84,89,94,99],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",3293,"2026-08-20T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":39},"Security","security",435,{"name":45,"slug":46,"count":47,"latest_published_at":48},"Policy","policy",210,"2026-08-19T09:32:27.000Z",{"name":50,"slug":51,"count":52,"latest_published_at":53},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":55,"slug":56,"count":57,"latest_published_at":58},"Hardware","hardware",140,"2026-08-19T18:25:42.000Z",{"name":60,"slug":61,"count":62,"latest_published_at":63},"Consumer Tech","consumer-tech",95,"2026-08-18T16:05:00.000Z",{"name":65,"slug":66,"count":67,"latest_published_at":68},"Science","science",90,"2026-08-19T18:41:02.000Z",{"name":70,"slug":71,"count":72,"latest_published_at":73},"Software","software",73,"2026-08-18T07:51:50.000Z",{"name":75,"slug":76,"count":77,"latest_published_at":78},"Dev Tools","dev-tools",69,"2026-08-18T04:00:00.000Z",{"name":80,"slug":81,"count":82,"latest_published_at":83},"Startups","startups",47,"2026-08-19T19:13:46.000Z",{"name":85,"slug":86,"count":87,"latest_published_at":88},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":90,"slug":91,"count":92,"latest_published_at":93},"General","general",33,"2026-08-18T22:18:13.000Z",{"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"]