Exploring the power of social hub services. - Qingyuan Gong; Yang Chen 001; Xiaolong Yu; Chao Xu; Zhichun Guo; Yu Xiao 001; Fehmi Ben Abdesslem; Xin Wang 002; Pan Hui 001 (World Wide Web, 2019)

GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction. - Zhichun Guo; Wenhao Yu 002; Chuxu Zhang; Meng Jiang 001; Nitesh V. Chawla (CIKM, 2020)

Improving Generalizability of Fake News Detection Methods using Propensity Score Matching. - Bo Ni; Zhichun Guo; Jianing Li; Meng Jiang 001 (CoRR, 2020)

Action Sequence Augmentation for Early Graph-based Anomaly Detection. - Tong Zhao 003; Bo Ni; Wenhao Yu 002; Zhichun Guo; Neil Shah; Meng Jiang 001 (CIKM, 2021)

Sentence-Permuted Paragraph Generation. - Wenhao Yu 002; Chenguang Zhu 001; Tong Zhao 003; Zhichun Guo; Meng Jiang 001 (EMNLP (1), 2021)

Few-Shot Graph Learning for Molecular Property Prediction. - Zhichun Guo; Chuxu Zhang; Wenhao Yu 002; John Herr; Olaf Wiest; Meng Jiang 001; Nitesh V. Chawla (WWW, 2021)

Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting. - Yihong Ma; Patrick Gérard; Yijun Tian 001; Zhichun Guo; Nitesh V. Chawla (CIKM, 2022)

RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Chao Huang 001; Ronald A. Metoyer; Nitesh V. Chawla (IJCAI, 2022)

Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Yihong Ma; Ronald A. Metoyer; Nitesh V. Chawla (IJCAI, 2022)

FakeEdge: Alleviate Dataset Shift in Link Prediction. - Kaiwen Dong; Yijun Tian 001; Zhichun Guo; Yang Yang 008; Nitesh V. Chawla (LoG, 2022)

Flashlight: Scalable Link Prediction With Effective Decoders. - Yiwei Wang 001; Bryan Hooi; Yozen Liu; Tong Zhao 003; Zhichun Guo; Neil Shah (LoG, 2022)

SD2: Slicing and Dicing Scholarly Data for Interactive Evaluation of Academic Performance. - Zhichun Guo; Jun Tao 002; Siming Chen 001; Nitesh V. Chawla; Chaoli Wang 001 (CoRR, 2022)

Graph-based Molecular Representation Learning. - Zhichun Guo; Bozhao Nan; Yijun Tian 001; Olaf Wiest; Chuxu Zhang; Nitesh V. Chawla (CoRR, 2022)

NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Xiangliang Zhang 001; Nitesh V. Chawla (CoRR, 2022)

Boosting Graph Neural Networks via Adaptive Knowledge Distillation. - Zhichun Guo; Chunhui Zhang; Yujie Fan; Yijun Tian 001; Chuxu Zhang; Nitesh V. Chawla (AAAI, 2023)

A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods. - Zhihan Zhang 001; Wenhao Yu 002; Mengxia Yu; Zhichun Guo; Meng Jiang 001 (EACL, 2023)

Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Xiangliang Zhang 001; Nitesh V. Chawla (ICLR, 2023)

Link Prediction with Non-Contrastive Learning. - William Shiao; Zhichun Guo; Tong Zhao 003; Evangelos E. Papalexakis; Yozen Liu; Neil Shah (ICLR, 2023)

Linkless Link Prediction via Relational Distillation. - Zhichun Guo; William Shiao; Shichang Zhang; Yozen Liu; Nitesh V. Chawla; Neil Shah; Tong Zhao 003 (ICML, 2023)

Graph-based Molecular Representation Learning. - Zhichun Guo; Kehan Guo; Bozhao Nan; Yijun Tian 001; Roshni G. Iyer; Yihong Ma; Olaf Wiest; Xiangliang Zhang 001; Wei Wang 010; Chuxu Zhang; Nitesh V. Chawla (IJCAI, 2023)

What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks. - Taicheng Guo; Kehan Guo; Bozhao Nan; Zhenwen Liang; Zhichun Guo; Nitesh V. Chawla; Olaf Wiest; Xiangliang Zhang 001 (NeurIPS, 2023)

What indeed can GPT models do in chemistry? A comprehensive benchmark on eight tasks. - Taicheng Guo; Kehan Guo; Bozhao Nan; Zhengwen Liang; Zhichun Guo; Nitesh V. Chawla; Olaf Wiest; Xiangliang Zhang 001 (CoRR, 2023)

SD2: Slicing and Dicing Scholarly Data for Interactive Evaluation of Academic Performance. - Zhichun Guo; Jun Tao 002; Siming Chen 001; Nitesh V. Chawla; Chaoli Wang 001 (IEEE Trans. Vis. Comput. Graph., 2023)

Pure Message Passing Can Estimate Common Neighbor for Link Prediction. - Kaiwen Dong; Zhichun Guo; Nitesh V. Chawla (NeurIPS, 2024)

Can LLMs Solve Molecule Puzzles? A Multimodal Benchmark for Molecular Structure Elucidation. - Kehan Guo; Bozhao Nan; Yujun Zhou 002; Taicheng Guo; Zhichun Guo; Mihir Surve; Zhenwen Liang; Nitesh V. Chawla; Olaf Wiest; Xiangliang Zhang 001 (NeurIPS, 2024)

How Does Message Passing Improve Collaborative Filtering? - Mingxuan Ju; William Shiao; Zhichun Guo; Yanfang Ye 001; Yozen Liu; Neil Shah; Tong Zhao 003 (NeurIPS, 2024)

Node Duplication Improves Cold-start Link Prediction. - Zhichun Guo; Tong Zhao 003; Yozen Liu; Kaiwen Dong; William Shiao; Neil Shah; Nitesh V. Chawla (CoRR, 2024)

Improving Out-of-Vocabulary Handling in Recommendation Systems. - William Shiao; Mingxuan Ju; Zhichun Guo; Xin Chen 085; Evangelos E. Papalexakis; Tong Zhao 003; Neil Shah; Yozen Liu (CoRR, 2024)

You do not have to train Graph Neural Networks at all on text-attributed graphs. - Kaiwen Dong; Zhichun Guo; Nitesh V. Chawla (CoRR, 2024)

CORE: Data Augmentation for Link Prediction via Information Bottleneck. - Kaiwen Dong; Zhichun Guo; Nitesh V. Chawla (CoRR, 2024)

MolX: Enhancing Large Language Models for Molecular Learning with A Multi-Modal Extension. - Khiem Le; Zhichun Guo; Kaiwen Dong; Xiaobao Huang; Bozhao Nan; Roshni G. Iyer; Xiangliang Zhang 001; Olaf Wiest; Wei Wang 010; Nitesh V. Chawla (CoRR, 2024)

YOSO: You-Only-Sample-Once via Compressed Sensing for Graph Neural Network Training. - Yi Li; Zhichun Guo; Guanpeng Li; Bingzhe Li (CoRR, 2024)

Improving Out-of-Vocabulary Hashing in Recommendation Systems. - William Shiao; Mingxuan Ju; Zhichun Guo; Xin Chen 085; Evangelos E. Papalexakis; Tong Zhao 003; Neil Shah; Yozen Liu (WWW (Companion Volume), 2025)

Universal Link Predictor By In-Context Learning on Graphs. - Kaiwen Dong; Haitao Mao; Zhichun Guo; Nitesh V. Chawla (Trans. Mach. Learn. Res., 2025)

Node Duplication Improves Cold-start Link Prediction. - Zhichun Guo; Tong Zhao 003; Yozen Liu; Kaiwen Dong; William Shiao; Mingxuan Ju; Neil Shah; Nitesh V. Chawla (Trans. Mach. Learn. Res., 2025)

Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond. - Kehan Guo; Yili Shen; Gisela Abigail Gonzalez-Montiel; Yue Huang 001; Yujun Zhou 002; Mihir Surve; Zhichun Guo; Prayel Das; Nitesh V. Chawla; Olaf Wiest; Xiangliang Zhang 001 (CoRR, 2025)

Improving Protein Sequence Design through Designability Preference Optimization. - Fanglei Xue; Andrew Kubaney; Zhichun Guo; Joseph K. Min; Ge Liu; Yi Yang; David Baker (CoRR, 2025)

ChemHGNN: A Hierarchical Hypergraph Neural Network for Reaction Virtual Screening and Discovery. - Xiaobao Huang; Yihong Ma; Anjali Gurajapu; Jules Schleinitz; Zhichun Guo; Sarah E. Reisman; Nitesh V. Chawla (CoRR, 2025)