5 papers
Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discovery
Guikun Xu, Xiaohan Yi, Ziqiao Meng +2
Exploring molecular energy landscapes and identifying ground-state conformations are central challenges in computational chemistry. However, generating diverse low-energy conformer…
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking
Yiqiang Yi, Xu Wan, Yatao Bian +2
Predicting the docking between proteins and ligands is a crucial and challenging task for drug discovery. However, traditional docking methods mainly rely on scoring functions, and…
Measuring Diversity in Synthetic Datasets
Yuchang Zhu, Huizhe Zhang, Bingzhe Wu +5
Large language models (LLMs) are widely adopted to generate synthetic datasets for various natural language processing (NLP) tasks, such as text classification and summarization. H…
Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization
Qingyang Zhang, Haitao Wu, Changqing Zhang +2
Existing methods to enhance the reasoning capability of large language models predominantly rely on supervised fine-tuning (SFT) followed by reinforcement learning (RL) on reasonin…
COME: Test-time adaption by Conservatively Minimizing Entropy
Qingyang Zhang, Yatao Bian, Xinke Kong +2
Machine learning models must continuously self-adjust themselves for novel data distribution in the open world. As the predominant principle, entropy minimization (EM) has been pro…