Can AI agents organize scientific investigations that lead to well-supported conclusions? To evaluate this capability, we introduce PhysClosureBench, a benchmark of 50 expert-verified, goal-specified research tasks spanning strong-field, attosecond, and neighboring physics areas. Each task specifies the research object...
Yi-Jia Mao, Song-Bin Dai, Tao Chen et al.· 0 citations
This work proposes Tool-Grounded Multi-Agent Reasoning for Compositional Chemical Problem Solving (TMCS), a step-by-step multi-agent framework that formalizes chemical problem solving as an interpretable, tool-augmented workflow.
Sheng-Qin Wang, Jie Jin, Yu Cheng et al.· 0 citations
Draft-OPD, which uses target-assisted rollout for stable continuations and replays drafting from the verification-exposed error positions, allowing the drafter to learn from target feedback on both accepted and rejected proposals, focusing on the draft-induced errors that limit speculative acceptance.
This work introduces a student reference KL loss and mask the advantages of special termination tokens to mitigate the problem of excessive generation length and frequent truncation, and improves on science benchmarks such as HLE and HiPhO, suggesting that OPD transfers reasoning capabilities that generalize beyond the...
Hao-Nan He, Hao Lei, Yun Luo et al.· 5 citations· ⚡1
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