Author

Kimin Lee

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#artificial intelligence Preprint Oct 2026

Learning Quality-Controllable Robot Policies with Iterative Hindsight Relabeling

Quality-Controllable Policy is introduced, a robot policy that enables inference-time control over both individual quality attributes and their combinations and their combinations, and an iterative hindsight relabeling loop is proposed to extend the controllable quality range beyond initial demonstrations.

Sinjae Kang, Dongyeeb Shin, Jae-Joon Kim et al. · 0 citations

#artificial intelligence Preprint Oct 2026

ACCRUE: Continual Off-Policy Reinforcement Learning for Robot Foundation Models

Reinforcement learning (RL) post-training improves robot foundation models (RFMs) beyond their demonstrations, but real-world deployment demands more: learning new tasks efficiently while retaining previously acquired behaviors. Existing continual RL methods on top of VLAs mitigate forgetting but rely on on-policy upda...

Changyeon Kim, Kimin Lee, Yashraj Narang et al. · 0 citations