6 papers · 1 filter
Equivariant Evidential Deep Learning for Interatomic Potentials
Zhongyao Wang, Taoyong Cui, Jiawen Zou +5
Uncertainty quantification (UQ) is critical for assessing the reliability of machine learning interatomic potentials (MLIPs) in molecular dynamics (MD) simulations, identifying ext…
Advanced Long-term Earth System Forecasting
Hao Wu, Yuan Gao, Ruijian Gou +30
Reliable long-term forecasting of Earth system dynamics is fundamentally limited by instabilities in current artificial intelligence (AI) models during extended autoregressive simu…
ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System
Dong Han, Zhehong Ai, Pengxiang Cai +16
Bayesian optimization (BO) is a powerful tool for scientific discovery in chemistry, yet its efficiency is often hampered by the sparse experimental data and vast search space. Her…
ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area
Junxian Li, Di Zhang, Xunzhi Wang +16
Large Language Models (LLMs) have achieved remarkable success and have been applied across various scientific fields, including chemistry. However, many chemical tasks require the…
ChemMLLM: Chemical Multimodal Large Language Model
Qian Tan, Dongzhan Zhou, Peng Xia +5
Multimodal large language models (MLLMs) have made impressive progress in many applications in recent years. However, chemical MLLMs that can handle cross-modal understanding and g…
Multimodal-Guided Dynamic Dataset Pruning for Robust and Efficient Data-Centric Learning
Suorong Yang, Peijia Li, Yujie Liu +5
Modern deep models are trained on large real-world datasets, where data quality varies and redundancy is common. Data-centric approaches such as dataset pruning have shown promise…