[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-new-benchmark-tests-llm-logic-with-tunable-complexity":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},1682,"new-benchmark-tests-llm-logic-with-tunable-complexity","New Benchmark Tests LLM Logic With Tunable Complexity","A new automated framework called QMFOL generates first-order logic puzzles with precise complexity controls, exposing where top reasoning models still stumble.","A research team has built a benchmark designed to stress-test how well large language models actually reason — rather than pattern-match their way to correct answers.\n\nThe framework, called QMFOL, generates deductive reasoning tasks grounded in monadic first-order logic. Researchers can dial up the difficulty by adjusting reasoning depth, breadth, label types, and the number of misleading distractors. The resulting benchmark, QMFOLBench, contains 2,880 test instances across 960 configurations. To keep the problems honest, the team uses a round-trip verification step: an external logic prover checks that any natural-language translation of a problem stays consistent with its underlying formal structure.\n\nThe findings matter because most existing benchmarks lose their usefulness fast — models train on the internet, and internet-adjacent test sets get contaminated or saturated. A framework that generates novel problems with tunable complexity is harder to game. The study also surfaces a concrete weakness: the six large reasoning models and two standard LLMs tested all degraded in performance as logical complexity rose, and all struggled more with False- and Unknown-labeled conclusions than with True ones — a sign that models may be defaulting to confirmation rather than genuine inference.\n\nThe sensitivity to semantic variation is worth watching. A model that aces a logic problem in one phrasing but fails a structurally identical one worded differently is not reasoning — it is retrieving.","[\"ai\",\"benchmarks\",\"llm\",\"reasoning\"]","2026-06-19T04:00:00.000Z","2026-06-19T09:51:16.043Z","2026-06-19T14:21:36.912Z","published",null,[],"ai",[24,26,27,28],"benchmarks","llm","reasoning",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.20227",0,{"sections":35},[36,39,43,48,53,58,63,67,71,76,81,86,91,96],{"name":37,"slug":24,"count":38,"latest_published_at":18},"AI",490,{"name":40,"slug":41,"count":42,"latest_published_at":18},"Security","security",132,{"name":44,"slug":45,"count":46,"latest_published_at":47},"Policy","policy",88,"2026-06-16T09:26:09.000Z",{"name":49,"slug":50,"count":51,"latest_published_at":52},"Consumer Tech","consumer-tech",78,"2026-06-16T17:58:24.000Z",{"name":54,"slug":55,"count":56,"latest_published_at":57},"Hardware","hardware",62,"2026-06-18T15:24:16.000Z",{"name":59,"slug":60,"count":61,"latest_published_at":62},"Deals","deals",58,"2026-06-19T14:43:50.000Z",{"name":64,"slug":65,"count":61,"latest_published_at":66},"Software","software","2026-06-16T20:00:00.000Z",{"name":68,"slug":69,"count":70,"latest_published_at":18},"Dev Tools","dev-tools",50,{"name":72,"slug":73,"count":74,"latest_published_at":75},"Science","science",38,"2026-06-18T04:00:00.000Z",{"name":77,"slug":78,"count":79,"latest_published_at":80},"Gaming","gaming",31,"2026-06-16T15:25:13.000Z",{"name":82,"slug":83,"count":84,"latest_published_at":85},"General","general",26,"2026-06-13T18:35:15.000Z",{"name":87,"slug":88,"count":89,"latest_published_at":90},"Startups","startups",23,"2026-06-16T15:00:00.000Z",{"name":92,"slug":93,"count":94,"latest_published_at":95},"Reviews","reviews",19,"2026-06-14T08:00:00.000Z",{"name":97,"slug":98,"count":99,"latest_published_at":100},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]