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cs.LG2026
Flow-based Policy With Distributional Reinforcement Learning in Trajectory Optimization
Ruijie Hao, Longfei Zhang, Yang Dai +3
Reinforcement Learning (RL) has proven highly effective in addressing complex control and decision-making tasks. However, in most traditional RL algorithms, the policy is typically…
cs.LG2025
Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching
Zhengyan Wan, Yidong Ouyang, Liyan Xie +3
Guidance provides a simple and effective framework for posterior sampling by steering the generation process towards the desired distribution. When modeling discrete data, existing…
cs.LG2024★ 2 cited
Transfer Learning for Diffusion Models
Yidong Ouyang, Liyan Xie, Hongyuan Zha +1
Diffusion models, a specific type of generative model, have achieved unprecedented performance in recent years and consistently produce high-quality synthetic samples. A critical p…