2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
Beyond Distributional Fidelity: Causal-Penalized Diffusion for Synthetic Tabular Data
Lan Tao, Yongxian He, Shirong Xu +2
Synthetic tabular generators are commonly optimized for distributional fidelity, but statistical similarity alone does not guarantee preservation of causal effects. In this paper,…
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…
Training-Free Self-Correction for Multimodal Masked Diffusion Models
Yidong Ouyang, Panwen Hu, Zhengyan Wan +7
Masked diffusion models have emerged as a powerful framework for text and multimodal generation. However, their sampling procedure updates multiple tokens simultaneously and treats…
Alignment of Diffusion Model and Flow Matching for Text-to-Image Generation
Yidong Ouyang, Liyan Xie, Hongyuan Zha +1
Diffusion models and flow matching have demonstrated remarkable success in text-to-image generation. While many existing alignment methods primarily focus on fine-tuning pre-traine…
Corrected Samplers for Discrete Flow Models
Zhengyan Wan, Yidong Ouyang, Liyan Xie +3
Discrete flow models (DFMs) have been proposed to learn the data distribution on finite state space, offering a flexible framework as an alternative to discrete diffusion models. A…