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Shijian Wang

2 accepted papers

2026

Optimal Transport for Reward Modeling from Noisy Feedback

ICML 2026poster

Reward models are fundamental to Reinforcement Learning from Human Feedback (RLHF), yet real-world datasets are inevitably corrupted by noisy preference. Conventional training objectives tend to overfit these errors, while existing denoising approaches often rely on homogeneous noise assumptions tha…

Cited by 0SourceScholar
2026

Synthetic Curriculum Reinforces Compositional Text-to-Image Generation

CVPR 2026

Text-to-Image (T2I) generation has long been an open problem, with compositional synthesis remaining particularly challenging. This task requires accurate rendering of complex scenes containing multiple objects that exhibit diverse attributes as well as intricate spatial and semantic relationships,

Cited by 0SourceScholar