7 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
Lower extremity exoskeletons designed for multi-joint assistance are increasingly explored for rehabilitation and human augmentation. However, conventional monoarticular designs often suffer from joint misalignment and actuator redundancy, limiting their efficiency and user comfort. This study prese…
Deep learning-based image watermarking, while robust against conventional distortions, remains vulnerable to advanced adversarial and regeneration attacks. Conventional countermeasures, which jointly optimize the encoder and decoder via a noise layer, face 2 inevitable challenges:(1) decrease of cle
Recent studies reveal that Large Language Models (LLMs) exhibit strong sequential reasoning capabilities, allowing them to replace specialized time-series models and serve as foundation models for complex time-series analysis. To activate the capabilities of LLMs for time-series tasks, numerous stud…
Control algorithms in production environments typically require domain experts to tune their parameters and logic for specific scenarios. However, existing research predominantly focuses on algorithmic performance under ideal or default configurations, overlooking the critical aspect of Tuning Poten…
Multi-task prompt learning has emerged as a promising technique for fine-tuning pre-trained Vision-Language Models (VLMs) to various downstream tasks. However, existing methods ignore challenges caused by spurious correlations and dynamic task relationships, which may reduce the model performance. T…
Current parameter-efficient fine-tuning (PEFT) methods have shown superior performance in continual learning. However, most existing PEFT-based methods focus on mitigating catastrophic forgetting by limiting modifications to the old task model caused by new tasks. This hinders backward knowledge tra…