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Sujie Hu

3 accepted papers

2026

$E^2$PO: Embedding-perturbed Exploration Preference Optimization for Flow Models

ICML 2026poster

Recent advancements have established Reinforcement Learning (RL) as a pivotal paradigm for aligning generative models with human intent. However, group-based optimization frameworks (e.g., GRPO) face a critical limitation: *the rapid decay of intra-group variance*. As the distinctiveness among sampl…

Cited by 0SourceScholar
2026

Taming Preference Mode Collapse via Directional Decoupling Alignment in Diffusion Reinforcement Learning

CVPR 2026

Recent studies have demonstrated significant progress in aligning text-to-image diffusion models with human preference via Reinforcement Learning from Human Feedback. However, while existing methods achieve high scores on automated reward metrics, they often lead to Preference Mode Collapse (PMC)-a

Cited by 0SourceScholar
2024

TOD3Cap: Towards 3D Dense Captioning in Outdoor Scenes

ECCV 2024poster

"3D dense captioning stands as a cornerstone in achieving a comprehensive understanding of 3D scenes through natural language. It has recently witnessed remarkable achievements, particularly in indoor settings. However, the exploration of 3D dense captioning in outdoor scenes is hindered by two majo…