activity
20242026
collaborators

5 papers

cs.CV2026

MolX: Enhancing Large Language Models for Molecular Understanding With A Multi-Modal Extension

Khiem Le, Zhichun Guo, Kaiwen Dong +8

Large Language Models (LLMs) with their strong task-handling capabilities have shown remarkable advancements across a spectrum of fields, moving beyond natural language understandi…

cs.LG2025

Node Duplication Improves Cold-start Link Prediction

Zhichun Guo, Tong Zhao, Yozen Liu +5

Graph Neural Networks (GNNs) are prominent in graph machine learning and have shown state-of-the-art performance in Link Prediction (LP) tasks. Nonetheless, recent studies show tha…

cs.LG2025

ChemHGNN: A Hierarchical Hypergraph Neural Network for Reaction Virtual Screening and Discovery

Xiaobao Huang, Yihong Ma, Anjali Gurajapu +4

Reaction virtual screening and discovery are fundamental challenges in chemistry and materials science, where traditional graph neural networks (GNNs) struggle to model multi-react…

cs.AI2025

Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond

Kehan Guo, Yili Shen, Gisela Abigail Gonzalez-Montiel +8

The rapid advent of machine learning (ML) and artificial intelligence (AI) has catalyzed major transformations in chemistry, yet the application of these methods to spectroscopic a…

cs.LG2024

Pure Message Passing Can Estimate Common Neighbor for Link Prediction

Kaiwen Dong, Zhichun Guo, Nitesh V. Chawla

Message Passing Neural Networks (MPNNs) have emerged as the {\em de facto} standard in graph representation learning. However, when it comes to link prediction, they often struggle…