7 papers
Language-Informed Flow Matching for Trend-Guided Structure-Based 3D Molecular Generation
Tianyu Gao, Zhikai Su, Jiashu Li +5
Structure-based drug design (SBDD) requires ligands that satisfy both 3D target affinity and 1D chemical validity. Existing controllable generation methods often rely on task-speci…
DiDPO: Diff-in-Diff Policy Optimization for Coding Agent Training
Xucong Wang, Zhe Zhao, Liheng Yu +3
Reinforcement learning with Verifiable Reward (RLVR) has emerged as a powerful paradigm for training coding agents, where the execution feedback from compilation and tests provides…
Universal and efficient graph neural networks with dynamic attention for machine learning interatomic potentials
Shuyu Bi, Zhede Zhao, Qiangchao Sun +3
The core of molecular dynamics simulation fundamentally lies in the interatomic potential. Traditional empirical potentials lack accuracy, while first-principles methods are comput…
Logos: An evolvable reasoning engine for rational molecular design
Haibin Wen, Zhe Zhao, Fanfu Wang +4
The discovery and design of functional molecules remain central challenges across chemistry,biology, and materials science. While recent advances in machine learning have accelerat…
FaLW: A Forgetting-aware Loss Reweighting for Long-tailed Unlearning
Liheng Yu, Zhe Zhao, Yuxuan Wang +4
Machine unlearning, which aims to efficiently remove the influence of specific data from trained models, is crucial for upholding data privacy regulations like the ``right to be fo…
Rethinking Crystal Symmetry Prediction: A Decoupled Perspective
Liheng Yu, Zhe Zhao, Xucong Wang +2
Efficiently and accurately determining the symmetry is a crucial step in the structural analysis of crystalline materials. Existing methods usually mindlessly apply deep learning m…