6 papers · 1 filter
LC-GRPO: Bridging Train-Inference Gap for Flow-Based GRPO with Langevin Correction
Yingqing Guo, Hui Yuan, Zijian He +2
Flow-based generative models are typically sampled by solving a deterministic ordinary differential equation (ODE), whereas online reinforcement learning requires stochastic rollou…
A First-order Generative Bilevel Optimization Framework for Diffusion Models
Quan Xiao, Hui Yuan, A F M Saif +4
Diffusion models, which iteratively denoise data samples to synthesize high-quality outputs, have achieved empirical success across domains. However, optimizing these models for do…
Training-Free Guidance Beyond Differentiability: Scalable Path Steering with Tree Search in Diffusion and Flow Models
Yingqing Guo, Yukang Yang, Hui Yuan +1
Training-free guidance enables controlled generation in diffusion and flow models, but most methods rely on gradients and assume differentiable objectives. This work focuses on tra…
Conversational Dueling Bandits in Generalized Linear Models
Shuhua Yang, Hui Yuan, Xiaoying Zhang +3
Conversational recommendation systems elicit user preferences by interacting with users to obtain their feedback on recommended commodities. Such systems utilize a multi-armed band…
Contractual Reinforcement Learning: Pulling Arms with Invisible Hands
Jibang Wu, Siyu Chen, Mengdi Wang +2
The agency problem emerges in today's large scale machine learning tasks, where the learners are unable to direct content creation or enforce data collection. In this work, we prop…
Diffusion Model for Data-Driven Black-Box Optimization
Zihao Li, Hui Yuan, Kaixuan Huang +4
Generative AI has redefined artificial intelligence, enabling the creation of innovative content and customized solutions that drive business practices into a new era of efficiency…