2 citations · 2 across the 4 of their papers we have counts for
4 papers
DLM-One: Diffusion Language Models for One-Step Sequence Generation
Tianqi Chen, Shujian Zhang, Mingyuan Zhou
This paper introduces DLM-One, a score-distillation-based framework for one-step sequence generation with continuous diffusion language models (DLMs). DLM-One eliminates iterative…
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models
Tianqi Chen, Shujian Zhang, Mingyuan Zhou
The machine learning community is increasingly recognizing the importance of fostering trust and safety in modern generative AI (GenAI) models. We posit machine unlearning (MU) as…
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
Shentao Yang, Tianqi Chen, Mingyuan Zhou
Aligning text-to-image diffusion model (T2I) with preference has been gaining increasing research attention. While prior works exist on directly optimizing T2I by preference data,…
Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts
Tianqi Chen, Yongfei Liu, Zhendong Wang +4
In light of the remarkable success of in-context learning in large language models, its potential extension to the vision domain, particularly with visual foundation models like St…