25 citations · 51 across the 5 of their papers we have counts for
6 papers
LLM: Multi-view Molecular Representation Learning with Large Language Models
Jiaxin Ju, Yizhen Zheng, Huan Yee Koh +2
Accurate molecular property prediction is a critical challenge with wide-ranging applications in chemistry, materials science, and drug discovery. Molecular representation methods,…
Collaborative Expert LLMs Guided Multi-Objective Molecular Optimization
Jiajun Yu, Yizhen Zheng, Huan Yee Koh +3
Molecular optimization is a crucial yet complex and time-intensive process that often acts as a bottleneck for drug development. Traditional methods rely heavily on trial and error…
Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials
Yizhen Zheng, Huan Yee Koh, Maddie Yang +5
The integration of Large Language Models (LLMs) into the drug discovery and development field marks a significant paradigm shift, offering novel methodologies for understanding dis…
PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection
Junjun Pan, Yixin Liu, Yizhen Zheng +1
Node-level graph anomaly detection (GAD) plays a critical role in identifying anomalous nodes from graph-structured data in various domains such as medicine, social networks, and e…
Large Language Models for Scientific Synthesis, Inference and Explanation
Yizhen Zheng, Huan Yee Koh, Jiaxin Ju +4
Large language models are a form of artificial intelligence systems whose primary knowledge consists of the statistical patterns, semantic relationships, and syntactical structures…
Integrating Graphs with Large Language Models: Methods and Prospects
Shirui Pan, Yizhen Zheng, Yixin Liu
Large language models (LLMs) such as GPT-4 have emerged as frontrunners, showcasing unparalleled prowess in diverse applications, including answering queries, code generation, and…