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cs.LG2026
Q-Learning with Scalar Adjoint Matching
Yonghoon Dong, Minsung Yoon, Jaehyuk Kim +3
Flow policies capture rich and diverse action distributions, and fine-tuning them with off-policy RL to improve beyond the demonstrations has drawn growing interest. However, fine-…
cs.LG2025
Debiasing Online Preference Learning via Preference Feature Preservation
Dongyoung Kim, Jinsung Yoon, Jinwoo Shin +1
Recent preference learning frameworks for large language models (LLMs) simplify human preferences with binary pairwise comparisons and scalar rewards. This simplification could mak…
cs.LG2025
MLE-STAR: Machine Learning Engineering Agent via Search and Targeted Refinement
Jaehyun Nam, Jinsung Yoon, Jiefeng Chen +3
Agents based on large language models (LLMs) for machine learning engineering (MLE) can automatically implement ML models via code generation. However, existing approaches to build…