[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-a-smarter-way-to-pick-examples-for-ai-pathology-models":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},4446,"a-smarter-way-to-pick-examples-for-ai-pathology-models","A Smarter Way to Pick Examples for AI Pathology Models","A training-free method called GAUC helps vision-language models read tissue slides more reliably by choosing better reference examples upfront.","AI pathology tools just got a quieter, cheaper fix for one of their most persistent problems.\n\nResearchers have proposed GAUC, a method for selecting the small set of image-text examples that guide vision-language models when diagnosing tissue samples — without retraining the model at all. The problem it targets is real: these models are notoriously sensitive to which examples you show them and how you phrase the question, meaning two nearly identical prompts can produce contradictory outputs. GAUC sidesteps costly fine-tuning by working directly in the model's existing embedding space, balancing three goals at once — keeping the selected examples representative of the full dataset, reducing sensitivity to how a query is worded, and penalizing examples that tend to produce uncertain or hallucinated answers. Tested on two public datasets, CRC-100K and MHIST, it matched the accuracy of stronger baselines while improving calibration and cutting hallucination rates.\n\nThis matters because annotated pathology data is scarce and expensive, making fine-tuning impractical for most clinical settings. A training-free method that also happens to reduce hallucinations — the failure mode that makes AI diagnostics genuinely dangerous — clears two obstacles at once. The calibration improvement is arguably more important than raw accuracy: a model that knows when it doesn't know is far safer in a diagnostic context.\n\nIn-context learning for medical AI is still a young field, and most prior work has optimized for accuracy alone. GAUC's focus on robustness and uncertainty is the more defensible engineering choice — though peer review and prospective clinical testing will determine whether these gains hold outside controlled benchmarks.","[\"ai\",\"machine learning\",\"healthcare\",\"computer vision\"]","2026-07-08T04:00:00.000Z","2026-07-08T09:37:04.655Z","2026-07-08T09:37:07.675Z","published",null,[],"ai",[24,26,27,28],"machine learning","healthcare","computer vision",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2605.18419",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"]