5 accepted papers
Lower-limb exoskeletons play an important role in improving gait symmetry and walking ability for hemiparetic patients. However, individual variability in gait symmetry and motor capability limits their assistive performance. To address this challenge, this paper proposes an Adaptive Coordinated Con
Adversarial examples crafted on one model often exhibit poor transferability to others, hindering their effectiveness in black-box settings. This limitation arises from two key factors: (i) \emph{decision-boundary variation} across models and (ii) \emph{representation drift} in feature space. We add…
The rapid adoption of large language models (LLMs) in diverse applications has intensified concerns over their security and integrity, especially in cloud environments where internal model parameters are inaccessible to users. Traditional tamper detection methods, designed for deterministic classifi…
The proliferation of Machine Learning as a Service (MLaaS) has enabled widespread deployment of large language models (LLMs) via cloud APIs, but also raises critical concerns about model integrity and security. Existing black-box tamper detection methods, such as watermarking and fingerprinting, rel
With the development of machine learning techniques, the attention of research has been moved from single-modal learning to multi-modal learning, as real-world data exist in the form of different modalities. However, multi-modal models often carry more information than single-modal models and they a…