3 papers
cs.LG2025
Efficient Controllable Diffusion via Optimal Classifier Guidance
Owen Oertell, Shikun Sun, Yiding Chen +3
The controllable generation of diffusion models aims to steer the model to generate samples that optimize some given objective functions. It is desirable for a variety of applicati…
cs.LG2025
Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions
Yiding Chen, Yiyi Zhang, Owen Oertell +1
Diffusion models accomplish remarkable success in data generation tasks across various domains. However, the iterative sampling process is computationally expensive. Consistency mo…
cs.LG2025
Avoiding scaling in RLHF through Preference-based Exploration
Mingyu Chen, Yiding Chen, Wen Sun +1
Reinforcement Learning from Human Feedback (RLHF) has emerged as a pivotal technique for large language model (LLM) alignment. This paper studies the setting of online RLHF and foc…