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cs.LG2026
Chem4DLLM: 4D Multimodal LLMs for Chemical Dynamics Understanding
Xinyu Li, Zhen Zhang, Qi Chen +3
Existing chemical understanding tasks primarily rely on static molecular representations, limiting their ability to model inherently dynamic phenomena such as bond breaking or conf…
cs.LG2024
Regularized Multi-LLMs Collaboration for Enhanced Score-based Causal Discovery
Xiaoxuan Li, Yao Liu, Ruoyu Wang +1
As the significance of understanding the cause-and-effect relationships among variables increases in the development of modern systems and algorithms, learning causality from obser…
cs.LG2024
Independence Constrained Disentangled Representation Learning from Epistemological Perspective
Ruoyu Wang, Lina Yao
Disentangled Representation Learning aims to improve the explainability of deep learning methods by training a data encoder that identifies semantically meaningful latent variables…