43 citations · 50 across the 7 of their papers we have counts for
7 papers
FAR-DPO: Feasibility-Aware and Robust Direct Preference Optimization for Cyclic Peptide Design
Guofeng Zhang, Rong Han, Xiaoyu Wang +4
Cyclic peptides are emerging as promising molecular scaffolds in drug discovery due to their high binding affinity and structural stability. However, extending generative models fr…
Towards World Models in Biomedical Research
Guangyu Wang, Jingkun Yue, Siqi Zhang +19
A central goal of biomedicine is to understand, predict and ultimately control the dynamic mechanisms by which biological systems respond to perturbations, disease progression and…
Learning to erase quantum states: thermodynamic implications of quantum learning theory
Haimeng Zhao, Yuzhen Zhang, John Preskill
The energy cost of erasing quantum states depends on our knowledge of the states. We show that learning algorithms can acquire such knowledge to erase many copies of an unknown sta…
Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation
Xiaohong Liu, Guoxing Yang, Yulin Luo +8
Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in medicine have shown potential in p…
CoPRA: Bridging Cross-domain Pretrained Sequence Models with Complex Structures for Protein-RNA Binding Affinity Prediction
Rong Han, Xiaohong Liu, Tong Pan +8
Accurately measuring protein-RNA binding affinity is crucial in many biological processes and drug design. Previous computational methods for protein-RNA binding affinity predictio…
TCM-GPT: Efficient Pre-training of Large Language Models for Domain Adaptation in Traditional Chinese Medicine
Guoxing Yang, Jianyu Shi, Zan Wang +2
Pre-training and fine-tuning have emerged as a promising paradigm across various natural language processing (NLP) tasks. The effectiveness of pretrained large language models (LLM…
ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation
Guangyu Wang, Guoxing Yang, Zongxin Du +2
Large language models have exhibited exceptional performance on various Natural Language Processing (NLP) tasks, leveraging techniques such as the pre-training, and instruction fin…