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Didan Deng

2 accepted papers

2026

Beyond VLM-Based Rewards: Diffusion-Native Latent Reward Modeling

ICML 2026poster

Preference optimization for diffusion models relies on reward functions that are both discriminative and computationally efficient. Vision-Language Models (VLMs) have emerged as powerful reward providers. However, their computation and memory cost can be substantial, and optimizing a latent diffusio…

Cited by 0SourceScholar
2024

Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models

NeurIPS 2024poster

Fine-tuning foundation models often compromises their robustness to distribution shifts. To remedy this, most robust fine-tuning methods aim to preserve the pre-trained features. However, not all pre-trained features are robust and those methods are largely indifferent to which ones to preserve. We…