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cs.LG2026
FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics
Qiran Zou, Hou Hei Lam, Wenhao Zhao +11
AI research agents accelerate ML research by automating hypothesis generation, experimentation, and empirical refinement. Existing agent strategies range from greedy hill-climbing…
cs.LG2026
LAPO: KL-Free Logit-Averaged Policy Optimization to Leverage RL and SFT in LLM Post-Training
Xingwei Gan, Ying Zhu
From a classical statistical perspective, model averaging and parameter shrinkage (e.g., Ridge regression with an -penalty) are deeply connected mechanisms designed to reduce…