2 citations · 2 across the 6 of their papers we have counts for
6 papers
Investigating Group Relative Policy Optimization for Diffusion Transformer based Text-to-Audio Generation
Yi Gu, Yanqing Liu, Chen Yang +1
Text-to-audio (T2A) generation has advanced considerably in recent years, yet existing methods continue to face challenges in accurately rendering complex text prompts, particularl…
Score Distillation of Flow Matching Models
Mingyuan Zhou, Yi Gu, Huangjie Zheng +5
Diffusion models achieve high-quality image generation but are limited by slow iterative sampling. Distillation methods alleviate this by enabling one- or few-step generation. Flow…
Few-Step Diffusion via Score identity Distillation
Mingyuan Zhou, Yi Gu, Zhendong Wang
Diffusion distillation has emerged as a promising strategy for accelerating text-to-image (T2I) diffusion models by distilling a pretrained score network into a one- or few-step ge…
Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step
Mingyuan Zhou, Huangjie Zheng, Yi Gu +2
Score identity Distillation (SiD) is a data-free method that has achieved SOTA performance in image generation by leveraging only a pretrained diffusion model, without requiring an…
Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization
Yi Gu, Zhendong Wang, Yueqin Yin +2
Aligning large language models with human preferences has emerged as a critical focus in language modeling research. Yet, integrating preference learning into Text-to-Image (T2I) g…
Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts
Yueqin Yin, Zhendong Wang, Yi Gu +3
In the field of large language models (LLMs), aligning models with the diverse preferences of users is a critical challenge. Direct Preference Optimization (DPO) has played a key r…