{"version":"1.0","type":"card","id":"19c5f572-cad6-4cf7-ac7a-bdf660792312","url":"https://stacklist.com/card/19c5f572-cad6-4cf7-ac7a-bdf660792312","title":"NEW AI paper worth bookmarking.","source_url":"https://www.linkedin.com/posts/omarsar_new-ai-paper-worth-bookmarking-this-is-share-7480322261594386432-nBaz/?utm_source=share&utm_medium=member_ios&rcm=ACoAAAI21ZsBNnZPaKuTab7nquKLCveUW7o-1DE","note":"This paper confirms that verification has emerged as a new important scaling axis in AI. It discusses the development of a training-free verifier that utilizes continuous scoring, showcasing significant accuracy across various benchmarks.","image":{"url":"https://ucarecdn.com/c05f30a6-78b0-4a02-9d4d-796abc6d9386/","alt":"NEW AI paper worth bookmarking.","width":1280,"height":800},"stack":{"id":"614ecd6d-12cd-4195-bf9c-3def755c89b2","title":"AI Inbox","url":"https://stacklist.com/stack/614ecd6d-12cd-4195-bf9c-3def755c89b2"},"created_at":"2026-07-08T00:05:06.094Z","updated_at":null,"aco":{"summary":"A new Stanford, NVIDIA, and UC Berkeley paper demonstrates verification as an emerging scaling axis for AI systems using LLMs as training-free verifiers that extract continuous calibrated scores from token logits. The approach achieves strong results across diverse benchmarks (86.5% on Terminal-Bench, 78.2% on SWE-Bench, 87.4% on RoboRewardBench) and enables iterative refinement in AI agents without fine-tuning.","tags":["ai-verification","llm-verifiers","scaling-axis","continuous-scoring","reward-models","agent-architecture"],"key_entities":[{"name":"Stanford","type":"organization","confidence":0.95},{"name":"NVIDIA","type":"organization","confidence":0.95},{"name":"UC Berkeley","type":"organization","confidence":0.95},{"name":"Elvis S.","type":"person","confidence":0.85},{"name":"LLM-as-Verifier","type":"technology","confidence":0.95},{"name":"SAC","type":"technology","confidence":0.85},{"name":"GRPO","type":"technology","confidence":0.85},{"name":"Claude Code","type":"technology","confidence":0.9},{"name":"verification-scaling","type":"concept","confidence":0.9},{"name":"continuous-reward-signals","type":"concept","confidence":0.9}],"classification":"analysis","language":"en","confidence":0.85,"provenance":{"model":"claude-haiku-4-5","tool":"@stacklist/be@0.1.0","confidence":0.85,"timestamp":"2026-07-08T00:05:13.320Z"},"token_counts":{"approximate":932,"cl100k":1108},"content_hash":"sha256:1450c2859fdf0a81b5b9e124aa66741a0831b474c35bc39f1380020b2bb23797","acp_version":"0.2","body_available":true,"body_tokens":932,"visibility":"public","agent_accessible":true,"status":"final"},"_links":{"self":"/api/public/card/19c5f572-cad6-4cf7-ac7a-bdf660792312.json","html":"https://stacklist.com/card/19c5f572-cad6-4cf7-ac7a-bdf660792312","md":"/api/public/card/19c5f572-cad6-4cf7-ac7a-bdf660792312.md","stack_json":"/api/public/stack/614ecd6d-12cd-4195-bf9c-3def755c89b2.json"}}