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Found 3 papers, 1 papers with code
Uncertainty-Aware Metabolic Stability Prediction with Dual-View Contrastive Learning
Despite recent advances in graph neural networks (GNNs) for MS prediction, current approaches face two critical limitations: (1) incomplete molecular modeling due to atom-centric message-passing mechanisms that disregard bond-level topological features, and (2) prediction frameworks that lack reliable uncertainty quantification.
Multi-Modality Representation Learning for Antibody-Antigen Interactions Prediction
While deep learning models play a crucial role in predicting antibody-antigen interactions (AAI), the scarcity of publicly available sequence-structure pairings constrains their generalization.
TrojanRobot: Physical-World Backdoor Attacks Against VLM-based Robotic Manipulation
To address this, we propose \textit{TrojanRobot}, a highly stealthy and broadly effective robotic backdoor attack in the physical world.
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