4 papers
One-Step Generative Policies with Q-Learning: A Reformulation of MeanFlow
Zeyuan Wang, Da Li, Yulin Chen +4
We introduce a one-step generative policy for offline reinforcement learning that maps noise directly to actions via a residual reformulation of MeanFlow, making it compatible with…
FoCLIP: A Feature-Space Misalignment Framework for CLIP-Based Image Manipulation and Detection
Yulin Chen, Zeyuan Wang, Tianyuan Yu +2
The well-aligned attribute of CLIP-based models enables its effective application like CLIPscore as a widely adopted image quality assessment metric. However, such a CLIP-based met…
Revisit the Imbalance Optimization in Multi-task Learning: An Experimental Analysis
Yihang Guo, Tianyuan Yu, Liang Bai +4
Multi-task learning (MTL) aims to build general-purpose vision systems by training a single network to perform multiple tasks jointly. While promising, its potential is often hinde…
COLA: Context-aware Language-driven Test-time Adaptation
Aiming Zhang, Tianyuan Yu, Liang Bai +5
Test-time adaptation (TTA) has gained increasing popularity due to its efficacy in addressing ``distribution shift'' issue while simultaneously protecting data privacy. However, mo…