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cs.LG2026
Scalable Maximum Entropy Reinforcement Learning for Diffusion Policies via Adjoint Matching
Serge Thilges, Onur Celik, Denis Blessing +2
Diffusion policies have recently emerged as a powerful paradigm for representing complex action distributions in reinforcement learning (RL). However, their application to online R…
cs.LG2026
VLA-FAIL: Efficient Task Failure Detection for Finetuned Vision-Language-Action Models
Florian Seligmann, Emiliyan Gospodinov, Enes Ulas Dincer +1
Vision-language-action models (VLAs) achieve state-of-the-art performance on many robotic manipulation tasks, yet they can still behave unpredictably in out-of-distribution scenari…
cs.LG2024
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
Onur Celik, Aleksandar Taranovic, Gerhard Neumann
Reinforcement learning (RL) is a powerful approach for acquiring a good-performing policy. However, learning diverse skills is challenging in RL due to the commonly used Gaussian p…