[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-ai-training-data-selection-tools-track-format-not-task":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},6859,"ai-training-data-selection-tools-track-format-not-task","AI Training Data Selection Tools Track Format Not Task","A new study finds gradient-based methods for selecting LLM training data track answer format more than task skill, undermining a common selection technique.","Gradient-based data attribution, a common tool for choosing AI training data, may be measuring formatting more than meaning.\n\nA new arXiv paper tests what gradient similarity, the technique behind data-selection tools like LESS, actually tracks when researchers pick examples for fine-tuning large language models. The team rendered the same benchmarks in different answer formats, letting them test task and format independently. Benchmark pairs that shared an answer format aligned strongly, with a disattenuated cosine similarity near 0.4, while the same benchmark rendered in a different format aligned barely at all, near 0.0, a pattern that held from the earliest pretraining checkpoints through post-training and across model sizes and families. When the researchers checked LESS's published data selections, they found each target example pulled in training data that shared its answer format, not necessarily its underlying task.\n\nThat is a problem for anyone treating gradient similarity as a stand-in for shared reasoning. If a multiple-choice question mostly attracts other multiple-choice questions regardless of subject, training sets curated this way may be less conceptually diverse than assumed, and performance gains credited to task relevance could actually be reward for matching format.\n\nSophisticated-looking math is not the same as math that measures what it claims to measure.","[\"ai\",\"machine-learning\",\"llm-training\",\"research\"]","2026-09-18T04:00:00.000Z","2026-09-18T19:50:40.153Z","2026-09-18T19:50:52.030Z","published",null,[],"ai",[24,26,27,28],"machine-learning","llm-training","research",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.19589",0,{"sections":35},[36,39,43,48,53,57,61,66,70,75,80,85,90,95],{"name":37,"slug":24,"count":38,"latest_published_at":18},"AI",4030,{"name":40,"slug":41,"count":42,"latest_published_at":18},"Security","security",654,{"name":44,"slug":45,"count":46,"latest_published_at":47},"Policy","policy",338,"2026-09-11T04:00:00.000Z",{"name":49,"slug":50,"count":51,"latest_published_at":52},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":54,"slug":55,"count":56,"latest_published_at":18},"Hardware","hardware",155,{"name":58,"slug":59,"count":60,"latest_published_at":18},"Science","science",121,{"name":62,"slug":63,"count":64,"latest_published_at":65},"Consumer Tech","consumer-tech",99,"2026-09-09T17:27:33.000Z",{"name":67,"slug":68,"count":69,"latest_published_at":18},"Dev Tools","dev-tools",78,{"name":71,"slug":72,"count":73,"latest_published_at":74},"Software","software",75,"2026-09-10T20:41:21.000Z",{"name":76,"slug":77,"count":78,"latest_published_at":79},"Startups","startups",55,"2026-09-09T23:14:29.000Z",{"name":81,"slug":82,"count":83,"latest_published_at":84},"Gaming","gaming",43,"2026-09-10T12:18:06.000Z",{"name":86,"slug":87,"count":88,"latest_published_at":89},"General","general",41,"2026-09-08T01:57:23.000Z",{"name":91,"slug":92,"count":93,"latest_published_at":94},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":96,"slug":97,"count":98,"latest_published_at":99},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]