3 papers
cs.LG2026
V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think
Bingda Tang, Yuhui Zhang, Xiaohan Wang +3
Aligning denoising generative models with human preferences or verifiable rewards remains a key challenge. While policy-gradient online reinforcement learning (RL) offers a princip…
cs.CV2026
Fine-tuning MLLMs Without Forgetting Is Easier Than You Think
He Li, Yuhui Zhang, Xiaohan Wang +2
The paper demonstrate that simple adjustments of the fine-tuning recipes of multimodal large language models (MLLM) are sufficient to mitigate catastrophic forgetting. On visual qu…
stat.ML2025
TULiP: Test-time Uncertainty Estimation via Linearization and Weight Perturbation
Yuhui Zhang, Dongshen Wu, Yuichiro Wada +1
A reliable uncertainty estimation method is the foundation of many modern out-of-distribution (OOD) detectors, which are critical for safe deployments of deep learning models in th…