Author

Jaehyuk Kim

2 papers indexed here

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#artificial intelligence May 2026

Trust Region Q Adjoint Matching

This paper introduces Trust Region Q Adjoint Matching (TRQAM), a stable off-policy fine-tuning algorithm that adaptively controls the path-space KL between the fine-tuned and pretrained policies through projected dual descent, achieving stable off-policy RL.

Yong Dong, Kyungmin Lee, Changyeon Kim et al. · arXiv.org · 6 citations · ⚡3

#artificial intelligence Preprint Oct 2026

Q-Learning with Scalar Adjoint Matching

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-tuning a flow policy against a learned value function is not trivial, because the policy generates its action over many flow steps. Adjoint...

Yong Dong, Minsung Yoon, Jaehyuk Kim et al. · 0 citations