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cs.LG2026
Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View
Yixian Xu, Yuanrui Zhang, Shengjie Luo +2
Reinforcement learning (RL) post-training provides a direct way to align diffusion models with human preferences and task-specific rewards. However, current RL algorithms for diffu…
cs.LG2026
In-Place Test-Time Training
Guhao Feng, Shengjie Luo, Kai Hua +4
The static ``train then deploy" paradigm fundamentally limits Large Language Models (LLMs) from dynamically adapting their weights in response to continuous streams of new informat…