On-policy distillation (OPD) has become increasingly popular for transferring teacher capabilities to student models. In this work, we ask a critical research question: Is on-policy sampling always beneficial for distilling arbitrary teacher-student pairs? We show that a simple alternative, Semi-OPD, which distills fro...
Siyan Zhao, Yong-Gan Fu, Jin-Dong Jiang et al.· 0 citations
Competent agents need precise and verifiable environments, such as sandboxes that are resumable at any stage and evolve from observable evidence. However, most long-horizon work exposes how rare these are: for example, an agent in medical research must ground a finding, classify it, and write a report over dozens of de...
Jun-Qi Liu, Yong-Yang Pan, Zhuo-Song Jiang et al.· 0 citations
Long-horizon agents are beginning to automate complete workflows that produce code, reports, and research artifacts. Medical imaging workflows are multi-stage and data-sensitive, while expert trajectories remain scarce and difficult to share. Structured benchmarks can localize failures through stage-level rubrics, but...
Junqi Liu, Yu-Fan He, Ye-Xiao He et al.· 0 citations
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