World models have emerged as powerful technology for facilitating policy learning in robotics by providing predictive representations of environmental dynamics. A crucial component of such models is the internal state representation, which serves as a bridge between observation, decision-making, and future state predic...
Li-Xuan Zhang, Meina Kan, Shiguang Shan et al.· IEEE Robotics and Automation...· 0 citations
Advances in multimodal understanding, reasoning, and tool use enable agents to tackle increasingly complex visual reasoning tasks. By distilling past execution experience into reusable skills, agents can transfer lessons from both successes and failures into future reasoning, reducing repeated errors and improving capa...
Bei Yan, Yue-Cong Min, Jie Zhang et al.· 0 citations
This work proposes a fine-grained alignment framework that couples dense reward signals at the data level with precise credit assignment at the algorithmic level to prevent response-level shared advantages from allowing local hallucinations to compromise all other valid outputs within the same response.
Xing-Ming Long, Jie Zhang, Yue-Cong Min et al.· 0 citations
Backdoor as Probe is proposed, a test-time adversarial defense for CLIP that improves average robust accuracy from 1.0\% to 52.3\% while retaining clean accuracy, achieving performance comparable to state-of-the-art methods with up to a \(5.7\times\) inference speedup.
Zhong Ling Wang, Jie Zhang, Sen Nie et al.· 0 citations
This work proposes O-Attack, a highly transferable black-box attack framework that outperforms six state-of-the-art methods in black-box transferability, with consistent effectiveness across prompts and improved efficiency and imperceptibility.
Sen Nie, Jie Zhang, Zhong Ling Wang et al.· 0 citations
