A Multi-Representation Ensemble Approach to Classifying Vocal Diseases. - Mingxuan Ju; Zhengkai Jiang 002; Yufan Chen; Soumya Ray (IEEE BigData, 2018)

Community Mitigation: A Data-driven System for COVID-19 Risk Assessment in a Hierarchical Manner. - Yanfang Ye 001; Yujie Fan; Shifu Hou; Yiming Zhang 002; Yiyue Qian; Shiyu Sun; Qian Peng; Mingxuan Ju; Wei Song; Kenneth A. Loparo (CIKM, 2020)

$ alpha$-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States. - Yanfang Ye 001; Shifu Hou; Yujie Fan; Yiming Zhang 002; Yiyue Qian; Shiyu Sun; Qian Peng; Mingxuan Ju; Wei Song; Kenneth A. Loparo (IEEE J. Biomed. Health Informatics, 2020)

Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond. - Shifu Hou; Yujie Fan; Mingxuan Ju; Yanfang Ye 001; Wenqiang Wan; Kui Wang; Yinming Mei; Qi Xiong; Fudong Shao (AAAI, 2021)

Heterogeneous Temporal Graph Transformer: An Intelligent System for Evolving Android Malware Detection. - Yujie Fan; Mingxuan Ju; Shifu Hou; Yanfang Ye 001; Wenqiang Wan; Kui Wang; Yinming Mei; Qi Xiong (KDD, 2021)

Dr.Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. - Mingxuan Ju; Wei Song; Shiyu Sun; Yanfang Ye 001; Yujie Fan; Shifu Hou; Kenneth A. Loparo; Liang Zhao 002 (WWW, 2021)

Heterogeneous Temporal Graph Neural Network. - Yujie Fan; Mingxuan Ju; Chuxu Zhang; Liang Zhao 002; Yanfang Ye 001 (CoRR, 2021)

Adaptive Kernel Graph Neural Network. - Mingxuan Ju; Shifu Hou; Yujie Fan; Jianan Zhao 002; Yanfang Ye 001; Liang Zhao 002 (AAAI, 2022)

Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering. - Mingxuan Ju; Wenhao Yu 002; Tong Zhao 003; Chuxu Zhang; Yanfang Ye 001 (EMNLP (Findings), 2022)

Heterogeneous Temporal Graph Neural Network. - Yujie Fan; Mingxuan Ju; Chuxu Zhang; Yanfang Ye 001 (SDM, 2022)

Black-box Node Injection Attack for Graph Neural Networks. - Mingxuan Ju; Yujie Fan; Yanfang Ye 001; Liang Zhao 002 (CoRR, 2022)

Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning. - Mingxuan Ju; Yujie Fan; Chuxu Zhang; Yanfang Ye 001 (AAAI, 2023)

Leveraging Comment Retrieval for Code Summarization. - Shifu Hou; Lingwei Chen; Mingxuan Ju; Yanfang Ye 001 (ECIR (2), 2023)

Generate rather than Retrieve: Large Language Models are Strong Context Generators. - Wenhao Yu 002; Dan Iter; Shuohang Wang; Yichong Xu; Mingxuan Ju; Soumya Sanyal 001; Chenguang Zhu 001; Michael Zeng 001; Meng Jiang 001 (ICLR, 2023)

Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. - Mingxuan Ju; Tong Zhao 003; Qianlong Wen; Wenhao Yu 002; Neil Shah; Yanfang Ye 001; Chuxu Zhang (ICLR, 2023)

Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization. - Chunhui Zhang; Yijun Tian 001; Mingxuan Ju; Zheyuan Liu 010; Yanfang Ye 001; Nitesh V. Chawla; Chuxu Zhang (ICLR, 2023)

GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation. - Mingxuan Ju; Tong Zhao 003; Wenhao Yu 002; Neil Shah; Yanfang Ye 001 (NeurIPS, 2023)

Self-Supervised Graph Structure Refinement for Graph Neural Networks. - Jianan Zhao 002; Qianlong Wen; Mingxuan Ju; Chuxu Zhang; Yanfang Ye 001 (WSDM, 2023)

Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions. - Zhihan Zhang 001; Wenhao Yu 002; Zheng Ning; Mingxuan Ju; Meng Jiang 001 (Trans. Assoc. Comput. Linguistics, 2023)

From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble. - Qianlong Wen; Mingxuan Ju; Zhongyu Ouyang; Chuxu Zhang; Yanfang Ye 001 (ICML, 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)

Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems. - Matthew Kolodner; Mingxuan Ju; Zihao Fan; Tong Zhao 003; Elham Ghazizadeh; Yan Wu; Neil Shah; Yozen Liu (RobustRecSys@RecSys, 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)

HARec: Hyperbolic Graph-LLM Alignment for Exploration and Exploitation in Recommender Systems. - Qiyao Ma; Menglin Yang 001; Mingxuan Ju; Tong Zhao 003; Neil Shah; Rex Ying (CoRR, 2024)

One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs. - Jingzhe Liu; Haitao Mao; Zhikai Chen; Wenqi Fan; Mingxuan Ju; Tong Zhao 003; Neil Shah; Jiliang Tang (CoRR, 2024)

Enhancing Item Tokenization for Generative Recommendation through Self-Improvement. - Runjin Chen; Mingxuan Ju; Ngoc Bui; Dimosthenis Antypas; Stanley Cai; Xiaopeng Wu; Leonardo Neves; Zhangyang Wang; Neil Shah; Tong Zhao 003 (CoRR, 2024)

MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation. - Zheyuan Zhang; Zehong Wang; Tianyi Ma; Varun Sameer Taneja; Sofia Nelson; Nhi Ha Lan Le; Keerthiram Murugesan; Mingxuan Ju; Nitesh V. Chawla; Chuxu Zhang; Yanfang Ye 001 (KDD (1), 2025)

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. - Donald Loveland; Xinyi Wu 003; Tong Zhao 003; Danai Koutra; Neil Shah; Mingxuan Ju (WWW, 2025)

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)

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. - Xinyi Wu 003; Donald Loveland; Runjin Chen; Yozen Liu; Xin Chen 085; Leonardo Neves; Ali Jadbabaie; Mingxuan Ju; Neil Shah; Tong Zhao 003 (WWW, 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)

Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics. - Jing Zhu 005; Mingxuan Ju; Yozen Liu; Danai Koutra; Neil Shah; Tong Zhao 003 (CoRR, 2025)

Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction. - Zongyue Qin; Shichang Zhang; Mingxuan Ju; Tong Zhao 003; Neil Shah; Yizhou Sun (CoRR, 2025)

On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. - Donald Loveland; Mingxuan Ju; Tong Zhao 003; Neil Shah; Danai Koutra (CoRR, 2025)

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. - Ngoc Bui; Menglin Yang 001; Runjin Chen; Leonardo Neves; Mingxuan Ju; Rex Ying; Neil Shah; Tong Zhao 003 (CoRR, 2025)

A Pre-training Framework for Relational Data with Information-theoretic Principles. - Quang Truong; Zhikai Chen; Mingxuan Ju; Tong Zhao 003; Neil Shah; Jiliang Tang (CoRR, 2025)

Non-parametric Graph Convolution for Re-ranking in Recommendation Systems. - Zhongyu Ouyang; Mingxuan Ju; Soroush Vosoughi; Yanfang Ye 001 (CoRR, 2025)