1 citations · 1 across the 2 of their papers we have counts for
8 papers
BadRobot: Jailbreaking Embodied LLM Agents in the Physical World
Hangtao Zhang, Chenyu Zhu, Xianlong Wang +9
Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language understanding abilities, has been extensi…
Towards Reliable Forgetting: A Survey on Machine Unlearning Verification
Lulu Xue, Shengshan Hu, Wei Lu +7
With growing demands for privacy protection, security, and legal compliance (e.g., GDPR), machine unlearning has emerged as a critical technique for ensuring the controllability an…
Dual-View Inference Attack: Machine Unlearning Amplifies Privacy Exposure
Lulu Xue, Shengshan Hu, Linqiang Qian +6
Machine unlearning is a newly popularized technique for removing specific training data from a trained model, enabling it to comply with data deletion requests. While it protects t…
HiF-DTA: Hierarchical Feature Learning Network for Drug-Target Affinity Prediction
Minghui Li, Yuanhang Wang, Peijin Guo +3
Accurate prediction of Drug-Target Affinity (DTA) is crucial for reducing experimental costs and accelerating early screening in computational drug discovery. While sequence-based…
ADVEDM:Fine-grained Adversarial Attack against VLM-based Embodied Agents
Yichen Wang, Hangtao Zhang, Hewen Pan +7
Vision-Language Models (VLMs), with their strong reasoning and planning capabilities, are widely used in embodied decision-making (EDM) tasks in embodied agents, such as autonomous…
Uncertainty-Aware Metabolic Stability Prediction with Dual-View Contrastive Learning
Peijin Guo, Minghui Li, Hewen Pan +6
Accurate prediction of molecular metabolic stability (MS) is critical for drug research and development but remains challenging due to the complex interplay of molecular interactio…