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Chenyuan Wu

3 accepted papers

2026

EditScore: Unlocking Online RL for Image Editing via High-Fidelity Reward Modeling

ICLR 2026poster

Instruction-guided image editing has achieved remarkable progress, yet current models still face challenges with complex instructions and often require multiple samples to produce a desired result. Reinforcement Learning (RL) offers a promising solution, but its adoption in image editing has been se…

Cited by 0SourcecodeScholar
2026

OmniGen2: Towards Instruction-Aligned Multimodal Generation

CVPR 2026

Multimodal generative models can process instructions in various modalities and demonstrate outstanding performance across a wide range of image generation tasks. However, their robustness in complex real-world scenarios remains limited due to insufficient generalized instruction alignment. We intro

Cited by 0SourcecodeScholar
2024

Mitigate Negative Transfer with Similarity Heuristic Lifelong Prompt Tuning

ACL 2024findings

Lifelong prompt tuning has significantly advanced parameter-efficient lifelong learning with its efficiency and minimal storage demands on various tasks.Our empirical studies, however, highlights certain transferability constraints in the current methodologies: a universal algorithm that guarantees…