5 citations · 10 across the 5 of their papers we have counts for
5 papers
A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
Ming Hu, Chenglong Ma, Wei Li +117
Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the compl…
TrialEnroll: Predicting Clinical Trial Enrollment Success with Deep & Cross Network and Large Language Models
Ling Yue, Sixue Xing, Jintai Chen +1
Clinical trials need to recruit a sufficient number of volunteer patients to demonstrate the statistical power of the treatment (e.g., a new drug) in curing a certain disease. Clin…
Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?
Kangyu Zheng, Yingzhou Lu, Zaixi Zhang +4
Currently, the field of structure-based drug design is dominated by three main types of algorithms: search-based algorithms, deep generative models, and reinforcement learning. Whi…
Graph Adversarial Diffusion Convolution
Songtao Liu, Jinghui Chen, Tianfan Fu +3
This paper introduces a min-max optimization formulation for the Graph Signal Denoising (GSD) problem. In this formulation, we first maximize the second term of GSD by introducing…
AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design
Xinze Li, Penglei Wang, Tianfan Fu +4
Structure-based drug design (SBDD), which aims to generate molecules that can bind tightly to the target protein, is an essential problem in drug discovery, and previous approaches…