Mingxuan Ju - RankMe

57 papers A* 14A 6Journal 30Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FlexRec: Adapting LLM-based Recommenders for Flexible Needs via Reinforcement Learning. CoRR Yijun Pan, Weikang Qiu, Qiyao Ma, Mingxuan Ju, Tong Zhao, Neil Shah, Rex Ying
2026	J	`jnl`	Plain Transformers are Surprisingly Powerful Link Predictors. CoRR Quang Truong, Yu Song, Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
2026	A	`conf`	Sequential Data Augmentation for Generative Recommendation. WSDM Geon Lee, Bhuvesh Kumar, Mingxuan Ju, Tong Zhao, Kijung Shin, Neil Shah, Liam Collins
2026	J	`jnl`	Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling. CoRR Xingyue Huang, Xueying Ding, Mingxuan Ju, Yozen Liu, Neil Shah, Tong Zhao
2025	J	`jnl`	A Pre-training Framework for Relational Data with Information-theoretic Principles. CoRR Quang Truong, Zhikai Chen, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
2025	J	`jnl`	Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics. CoRR Jing Zhu, Mingxuan Ju, Yozen Liu, Danai Koutra, Neil Shah, Tong Zhao
2025	A*	`conf`	GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. WWW Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Mingxuan Ju, Neil Shah, Tong Zhao
2025	J	`jnl`	Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction. CoRR Zongyue Qin, Shichang Zhang, Mingxuan Ju, Tong Zhao, Neil Shah, Yizhou Sun
2025	J	`jnl`	Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings. CoRR Xueying Ding, Xingyue Huang, Mingxuan Ju, Liam Collins, Yozen Liu, Leman Akoglu, Neil Shah, Tong Zhao
2025	—	`conf`	Improving Out-of-Vocabulary Hashing in Recommendation Systems. WWW (Companion Volume) William Shiao, Mingxuan Ju, Zhichun Guo, Xin Chen, Evangelos E. Papalexakis, Tong Zhao, Neil Shah, Yozen Liu
2025	A*	`conf`	Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. ICML Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao
2025	J	`jnl`	Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. CoRR Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao
2025	A	`conf`	MI4Rec: Pretrained Language Model based Cold-Start Recommendation with Meta-Item Embeddings. CIKM Zaiyi Zheng, Yaochen Zhu, Haochen Liu, Mingxuan Ju, Tong Zhao, Neil Shah, Jundong Li
2025	—	`conf`	MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation. KDD (1) 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
2025	J	`jnl`	Node Duplication Improves Cold-start Link Prediction. Trans. Mach. Learn. Res. Zhichun Guo, Tong Zhao, Yozen Liu, Kaiwen Dong, William Shiao, Mingxuan Ju, Neil Shah, Nitesh V. Chawla
2025	A	`conf`	Non-parametric Graph Convolution for Re-ranking in Recommendation Systems. RecSys Zhongyu Ouyang, Mingxuan Ju, Soroush Vosoughi, Yanfang Ye
2025	J	`jnl`	Non-parametric Graph Convolution for Re-ranking in Recommendation Systems. CoRR Zhongyu Ouyang, Mingxuan Ju, Soroush Vosoughi, Yanfang Ye
2025	—	`conf`	On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. KDD (2) Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Danai Koutra
2025	J	`jnl`	On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. CoRR Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Danai Koutra
2025	A*	`conf`	Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. WWW Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju
2024	J	`jnl`	Enhancing Item Tokenization for Generative Recommendation through Self-Improvement. CoRR Runjin Chen, Mingxuan Ju, Ngoc Bui, Dimosthenis Antypas, Stanley Cai, Xiaopeng Wu, Leonardo Neves, Zhangyang Wang, Neil Shah, Tong Zhao
2024	A*	`conf`	From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble. ICML Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, Yanfang Ye
2024	J	`jnl`	HARec: Hyperbolic Graph-LLM Alignment for Exploration and Exploitation in Recommender Systems. CoRR Qiyao Ma, Menglin Yang, Mingxuan Ju, Tong Zhao, Neil Shah, Rex Ying
2024	A*	`conf`	How Does Message Passing Improve Collaborative Filtering? NeurIPS Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, Tong Zhao
2024	J	`jnl`	How Does Message Passing Improve Collaborative Filtering? CoRR Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, Tong Zhao
2024	J	`jnl`	Improving Out-of-Vocabulary Handling in Recommendation Systems. CoRR William Shiao, Mingxuan Ju, Zhichun Guo, Xin Chen, Evangelos E. Papalexakis, Tong Zhao, Neil Shah, Yozen Liu
2024	J	`jnl`	MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation. CoRR 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
2024	J	`jnl`	One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs. CoRR Jingzhe Liu, Haitao Mao, Zhikai Chen, Wenqi Fan, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
2024	—	`conf`	Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems. RobustRecSys@RecSys Matthew Kolodner, Mingxuan Ju, Zihao Fan, Tong Zhao, Elham Ghazizadeh, Yan Wu, Neil Shah, Yozen Liu
2024	J	`jnl`	Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems. CoRR Matthew Kolodner, Mingxuan Ju, Zihao Fan, Tong Zhao, Elham Ghazizadeh, Yan Wu, Neil Shah, Yozen Liu
2024	J	`jnl`	Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. CoRR Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju
2023	A*	`conf`	Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization. ICLR Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang
2023	J	`jnl`	Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions. CoRR Zhihan Zhang, Wenhao Yu, Zheng Ning, Mingxuan Ju, Meng Jiang
2023	J	`jnl`	Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions. Trans. Assoc. Comput. Linguistics Zhihan Zhang, Wenhao Yu, Zheng Ning, Mingxuan Ju, Meng Jiang
2023	A*	`conf`	Generate rather than Retrieve: Large Language Models are Strong Context Generators. ICLR Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang
2023	A*	`conf`	GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation. NeurIPS Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye
2023	J	`jnl`	GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation. CoRR Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye
2023	A*	`conf`	Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning. AAAI Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye
2023	—	`conf`	Leveraging Comment Retrieval for Code Summarization. ECIR (2) Shifu Hou, Lingwei Chen, Mingxuan Ju, Yanfang Ye
2023	A*	`conf`	Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. ICLR Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang
2023	A	`conf`	Self-Supervised Graph Structure Refinement for Graph Neural Networks. WSDM Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, Yanfang Ye
2022	A*	`conf`	Adaptive Kernel Graph Neural Network. AAAI Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Yanfang Ye, Liang Zhao
2022	J	`jnl`	Black-box Node Injection Attack for Graph Neural Networks. CoRR Mingxuan Ju, Yujie Fan, Yanfang Ye, Liang Zhao
2022	J	`jnl`	Generate rather than Retrieve: Large Language Models are Strong Context Generators. CoRR Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang
2022	—	`conf`	Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering. EMNLP (Findings) Mingxuan Ju, Wenhao Yu, Tong Zhao, Chuxu Zhang, Yanfang Ye
2022	J	`jnl`	Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering. CoRR Mingxuan Ju, Wenhao Yu, Tong Zhao, Chuxu Zhang, Yanfang Ye
2022	A	`conf`	Heterogeneous Temporal Graph Neural Network. SDM Yujie Fan, Mingxuan Ju, Chuxu Zhang, Yanfang Ye
2022	J	`jnl`	Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning. CoRR Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye
2022	J	`jnl`	Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. CoRR Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang
2021	J	`jnl`	Adaptive Kernel Graph Neural Network. CoRR Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Liang Zhao, Yanfang Ye
2021	A*	`conf`	Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond. AAAI Shifu Hou, Yujie Fan, Mingxuan Ju, Yanfang Ye, Wenqiang Wan, Kui Wang, Yinming Mei, Qi Xiong, Fudong Shao
2021	A*	`conf`	Dr.Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. WWW Mingxuan Ju, Wei Song, Shiyu Sun, Yanfang Ye, Yujie Fan, Shifu Hou, Kenneth A. Loparo, Liang Zhao
2021	J	`jnl`	Heterogeneous Temporal Graph Neural Network. CoRR Yujie Fan, Mingxuan Ju, Chuxu Zhang, Liang Zhao, Yanfang Ye
2021	A*	`conf`	Heterogeneous Temporal Graph Transformer: An Intelligent System for Evolving Android Malware Detection. KDD Yujie Fan, Mingxuan Ju, Shifu Hou, Yanfang Ye, Wenqiang Wan, Kui Wang, Yinming Mei, Qi Xiong
2020	J	`jnl`	$\alpha$-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States. IEEE J. Biomed. Health Informatics Yanfang Ye, Shifu Hou, Yujie Fan, Yiming Zhang, Yiyue Qian, Shiyu Sun, Qian Peng, Mingxuan Ju, Wei Song, Kenneth A. Loparo
2020	A	`conf`	Community Mitigation: A Data-driven System for COVID-19 Risk Assessment in a Hierarchical Manner. CIKM Yanfang Ye, Yujie Fan, Shifu Hou, Yiming Zhang, Yiyue Qian, Shiyu Sun, Qian Peng, Mingxuan Ju, Wei Song, Kenneth A. Loparo
2018	—	`conf`	A Multi-Representation Ensemble Approach to Classifying Vocal Diseases. IEEE BigData Mingxuan Ju, Zhengkai Jiang, Yufan Chen, Soumya Ray