1 citations · 1 across the 2 of their papers we have counts for
4 papers
A Survey on Self-Improving Test-Time Intelligence: Feedback-Driven Adapting, Learning, and Scaling at Inference
Shuaicheng Niu, Guohao Chen, Yaofo Chen +14
The ability of AI systems to improve their behavior during deployment is becoming increasingly important. As inference moves beyond the static execution of a fixed trained model, a…
Continual Knowledge Adaptation for Reinforcement Learning
Jinwu Hu, Zihao Lian, Zhiquan Wen +5
Reinforcement Learning enables agents to learn optimal behaviors through interactions with environments. However, real-world environments are typically non-stationary, requiring ag…
Physics-Driven Spatiotemporal Modeling for AI-Generated Video Detection
Shuhai Zhang, ZiHao Lian, Jiahao Yang +6
AI-generated videos have achieved near-perfect visual realism (e.g., Sora), urgently necessitating reliable detection mechanisms. However, detecting such videos faces significant c…
Towards Efficient Task-Driven Model Reprogramming with Foundation Models
Shoukai Xu, Jiangchao Yao, Ran Luo +5
Vision foundation models exhibit impressive power, benefiting from the extremely large model capacity and broad training data. However, in practice, downstream scenarios may only s…