publications

2026

1. RecSys

   Understanding ID-Text Complementarity in Sequential Recommendation

   Liam Collins, Bhuvesh Kumar, Mingxuan Ju, Tong Zhao, Donald Loveland, Leonardo Neves, and Neil Shah

   In Proceedings of the 20th ACM Conference on Recommender Systems (RecSys), 2026

   arXiv Bib

   @inproceedings{collins2026idtext,
     title = {Understanding ID-Text Complementarity in Sequential Recommendation},
     author = {Collins, Liam and Kumar, Bhuvesh and Ju, Mingxuan and Zhao, Tong and Loveland, Donald and Neves, Leonardo and Shah, Neil},
     booktitle = {Proceedings of the 20th ACM Conference on Recommender Systems (RecSys)},
     year = {2026},
   }

2. RecSys

   Beyond Fixed Depths and Widths: Optimizing Textual Decoding Tries in LLM-based Generative Recommendation

   Jingzhe Liu, Hanbing Wang, Jiliang Tang, Liam Collins, Tong Zhao, Neil Shah, and Mingxuan Ju

   In Proceedings of the 20th ACM Conference on Recommender Systems (RecSys), 2026

   Bib

   @inproceedings{liu2026tries,
     title = {Beyond Fixed Depths and Widths: Optimizing Textual Decoding Tries in LLM-based Generative Recommendation},
     author = {Liu, Jingzhe and Wang, Hanbing and Tang, Jiliang and Collins, Liam and Zhao, Tong and Shah, Neil and Ju, Mingxuan},
     booktitle = {Proceedings of the 20th ACM Conference on Recommender Systems (RecSys)},
     year = {2026},
   }

3. KDD

   Understanding Generative Recommendation with Semantic IDs from a Model-scaling View

   Jingzhe Liu, Liam Collins, Jiliang Tang, Tong Zhao, Neil Shah, and Mingxuan Ju

   In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026

   arXiv Bib

   @inproceedings{liu2026scaling,
     title = {Understanding Generative Recommendation with Semantic IDs from a Model-scaling View},
     author = {Liu, Jingzhe and Collins, Liam and Tang, Jiliang and Zhao, Tong and Shah, Neil and Ju, Mingxuan},
     booktitle = {Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
     year = {2026},
   }

4. KDD

   Breaking Information Cocoons: A Hyperbolic Framework for Balancing Exploration and Exploitation in Recommender Systems

   Qiyao Ma, Menglin Yang, Mingxuan Ju, Tong Zhao, Neil Shah, and Rex Ying

   In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026

   arXiv Bib

   @inproceedings{ma2026cocoons,
     title = {Breaking Information Cocoons: A Hyperbolic Framework for Balancing Exploration and Exploitation in Recommender Systems},
     author = {Ma, Qiyao and Yang, Menglin and Ju, Mingxuan and Zhao, Tong and Shah, Neil and Ying, Rex},
     booktitle = {Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
     year = {2026},
   }

5. ICML

   Plain Transformers are Surprisingly Powerful Link Predictors

   Quang Truong, Yu Song, Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, and Jiliang Tang

   In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026

   arXiv Bib

   @inproceedings{truong2026transformers,
     title = {Plain Transformers are Surprisingly Powerful Link Predictors},
     author = {Truong, Quang and Song, Yu and Loveland, Donald and Ju, Mingxuan and Zhao, Tong and Shah, Neil and Tang, Jiliang},
     booktitle = {Proceedings of the 43rd International Conference on Machine Learning (ICML)},
     year = {2026},
   }

6. ACL

   MemRec: Collaborative Memory-Augmented Agentic Recommender System

   Weixin Chen, Yuhan Zhao, Jingyuan Huang, Zihe Ye, Mingxuan Ju, Tong Zhao, Neil Shah, Li Chen, and Yongfeng Zhang

   In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026

   arXiv Bib

   @inproceedings{chen2026memrec,
     title = {MemRec: Collaborative Memory-Augmented Agentic Recommender System},
     author = {Chen, Weixin and Zhao, Yuhan and Huang, Jingyuan and Ye, Zihe and Ju, Mingxuan and Zhao, Tong and Shah, Neil and Chen, Li and Zhang, Yongfeng},
     booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL)},
     year = {2026},
   }

7. ACL

   Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings

   Xueying Ding, Xingyue Huang, Mingxuan Ju, Liam Collins, Yozen Liu, Leman Akoglu, Neil Shah, and Tong Zhao

   In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026

   arXiv Bib

   @inproceedings{ding2026prepending,
     title = {Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings},
     author = {Ding, Xueying and Huang, Xingyue and Ju, Mingxuan and Collins, Liam and Liu, Yozen and Akoglu, Leman and Shah, Neil and Zhao, Tong},
     booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL)},
     year = {2026},
   }

8. ACL

   Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling

   Xingyue Huang, Xueying Ding, Mingxuan Ju, Yozen Liu, Neil Shah, and Tong Zhao

   In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026

   arXiv Bib

   @inproceedings{huang2026threshold,
     title = {Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling},
     author = {Huang, Xingyue and Ding, Xueying and Ju, Mingxuan and Liu, Yozen and Shah, Neil and Zhao, Tong},
     booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL)},
     year = {2026},
   }

9. SIGIR

   Semantic IDs for Recommender Systems at Snapchat: Use Cases, Technical Challenges, and Design Choices

   Mingxuan Ju^*, Tong Zhao^*, Leonardo Neves, Liam Collins, Bhuvesh Kumar, Jiwen Ren, Lili Zhang, Wenfeng Zhuo, Vincent Zhang, Xiao Bai, Jinchao Li, Karthik Iyer, Zihao Fan, Yilun Xu, Yiwen Chen, Peicheng Yu, Manish Malik, and Neil Shah

   In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2026

   arXiv Bib

   @inproceedings{ju2026semanticids,
     title = {Semantic IDs for Recommender Systems at Snapchat: Use Cases, Technical Challenges, and Design Choices},
     author = {Ju, Mingxuan and Zhao, Tong and Neves, Leonardo and Collins, Liam and Kumar, Bhuvesh and Ren, Jiwen and Zhang, Lili and Zhuo, Wenfeng and Zhang, Vincent and Bai, Xiao and Li, Jinchao and Iyer, Karthik and Fan, Zihao and Xu, Yilun and Chen, Yiwen and Yu, Peicheng and Malik, Manish and Shah, Neil},
     booktitle = {Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)},
     year = {2026},
   }

10. SIGIR

    Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics

    Jing Zhu, Mingxuan Ju, Yozen Liu, Danai Koutra, Neil Shah, and Tong Zhao

    In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2026

    arXiv Bib

    @inproceedings{zhu2026multimodal,
      title = {Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics},
      author = {Zhu, Jing and Ju, Mingxuan and Liu, Yozen and Koutra, Danai and Shah, Neil and Zhao, Tong},
      booktitle = {Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)},
      year = {2026},
    }

11. WSDM

    Sequential Data Augmentation for Generative Recommendation

    Geon Lee, Bhuvesh Kumar, Mingxuan Ju, Tong Zhao, Kijung Shin, Neil Shah, and Liam Collins

    In Proceedings of the 19th ACM International Conference on Web Search and Data Mining (WSDM), 2026

    arXiv Bib

    @inproceedings{lee2026augmentation,
      title = {Sequential Data Augmentation for Generative Recommendation},
      author = {Lee, Geon and Kumar, Bhuvesh and Ju, Mingxuan and Zhao, Tong and Shin, Kijung and Shah, Neil and Collins, Liam},
      booktitle = {Proceedings of the 19th ACM International Conference on Web Search and Data Mining (WSDM)},
      year = {2026},
    }

12. arXiv

    Self-supervised User Profile Generation for Personalization

    Mingxuan Ju, Yuwei Qiu, Tong Zhao, and Neil Shah

    arXiv preprint, 2026

    arXiv Bib

    @article{ju2026profile,
      title = {Self-supervised User Profile Generation for Personalization},
      author = {Ju, Mingxuan and Qiu, Yuwei and Zhao, Tong and Shah, Neil},
      journal = {arXiv preprint},
      year = {2026},
    }

13. arXiv

    Expressiveness Limits of Autoregressive Semantic ID Generation in Generative Recommendation

    Yupeng Hou, Haven Kim, Mingxuan Ju, Eduardo Escoto, Neil Shah, and Julian McAuley

    arXiv preprint, 2026

    arXiv Bib

    @article{hou2026expressiveness,
      title = {Expressiveness Limits of Autoregressive Semantic ID Generation in Generative Recommendation},
      author = {Hou, Yupeng and Kim, Haven and Ju, Mingxuan and Escoto, Eduardo and Shah, Neil and McAuley, Julian},
      journal = {arXiv preprint},
      year = {2026},
    }

14. arXiv

    MLPs are Efficient Distilled Generative Recommenders

    Zitian Guo, Yupeng Hou, Mingxuan Ju, Neil Shah, and Julian McAuley

    arXiv preprint, 2026

    arXiv Bib

    @article{guo2026mlps,
      title = {MLPs are Efficient Distilled Generative Recommenders},
      author = {Guo, Zitian and Hou, Yupeng and Ju, Mingxuan and Shah, Neil and McAuley, Julian},
      journal = {arXiv preprint},
      year = {2026},
    }

2025

1. LOG

   Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction

   Zongyue Qin, Shichang Zhang, Mingxuan Ju, Tong Zhao, Neil Shah, and Yizhou Sun

   In Proceedings of the Fourth Learning on Graphs Conference (LOG), 2025

   arXiv Bib

   @inproceedings{qin2025heuristic,
     title = {Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction},
     author = {Qin, Zongyue and Zhang, Shichang and Ju, Mingxuan and Zhao, Tong and Shah, Neil and Sun, Yizhou},
     booktitle = {Proceedings of the Fourth Learning on Graphs Conference (LOG)},
     year = {2025},
   }

2. NeurIPS

   A Pre-training Framework for Relational Data with Information-theoretic Principles

   Quang Truong, Zhikai Chen, Mingxuan Ju, Tong Zhao, Neil Shah, and Jiliang Tang

   In Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS), 2025

   arXiv Bib

   @inproceedings{truong2025relational,
     title = {A Pre-training Framework for Relational Data with Information-theoretic Principles},
     author = {Truong, Quang and Chen, Zhikai and Ju, Mingxuan and Zhao, Tong and Shah, Neil and Tang, Jiliang},
     booktitle = {Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS)},
     year = {2025},
   }

3. CIKM

   MI4Rec: Pretrained Language Model based Cold-Start Recommendation with Meta-Item Embeddings

   Zaiyi Zheng, Yaochen Zhu, Haochen Liu, Mingxuan Ju, Tong Zhao, Neil Shah, and Jundong Li

   In Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM), 2025

   Bib

   @inproceedings{zheng2025mi4rec,
     title = {MI4Rec: Pretrained Language Model based Cold-Start Recommendation with Meta-Item Embeddings},
     author = {Zheng, Zaiyi and Zhu, Yaochen and Liu, Haochen and Ju, Mingxuan and Zhao, Tong and Shah, Neil and Li, Jundong},
     booktitle = {Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM)},
     year = {2025}
   }

4. CIKM

   Generative Recommendation with Semantic IDs: A Practitioner’s Handbook

   Mingxuan Ju, Liam Collins, Leonardo Neves, Bhuvesh Kumar, Yufeng Wang, Tong Zhao, and Neil Shah

   In Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM), 2025

   Best Paper Award arXiv Bib Code

   Best Paper Award at CIKM 2025

   @inproceedings{ju2025grid,
     title = {Generative Recommendation with Semantic IDs: A Practitioner's Handbook},
     author = {Ju, Mingxuan and Collins, Liam and Neves, Leonardo and Kumar, Bhuvesh and Wang, Yufeng and Zhao, Tong and Shah, Neil},
     booktitle = {Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM)},
     year = {2025},
   }

5. RecSys

   Non-parametric Graph Convolution for Re-ranking in Recommendation Systems

   Zhongyu Ouyang^*, Mingxuan Ju^*, Soroush Vosoughi, and Yanfang Ye

   In Proceedings of the 19th ACM Conference on Recommender Systems (RecSys), 2025

   arXiv Bib

   @inproceedings{ouyang2025reranking,
     title = {Non-parametric Graph Convolution for Re-ranking in Recommendation Systems},
     author = {Ouyang, Zhongyu and Ju, Mingxuan and Vosoughi, Soroush and Ye, Yanfang},
     booktitle = {Proceedings of the 19th ACM Conference on Recommender Systems (RecSys)},
     year = {2025},
   }

6. KDD

   On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective

   Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, and Danai Koutra

   In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025

   arXiv Bib Code

   @inproceedings{loveland2025weightdecay,
     title = {On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective},
     author = {Loveland, Donald and Ju, Mingxuan and Zhao, Tong and Shah, Neil and Koutra, Danai},
     booktitle = {Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
     year = {2025},
   }

7. KDD

   Revisiting Self-Attention for Cross-Domain Sequential Recommendation

   Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Ching Dou, Sohail Nizam, Sen Yang, and Neil Shah

   In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025

   arXiv Bib Code

   @inproceedings{ju2025autocdsr,
     title = {Revisiting Self-Attention for Cross-Domain Sequential Recommendation},
     author = {Ju, Mingxuan and Neves, Leonardo and Kumar, Bhuvesh and Collins, Liam and Zhao, Tong and Qiu, Yuwei and Dou, Ching and Nizam, Sohail and Yang, Sen and Shah, Neil},
     booktitle = {Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
     year = {2025},
   }

8. KDD

   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, and Yanfang Ye

   In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025

   arXiv Bib

   @inproceedings{zhang2025mopi,
     title = {MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation},
     author = {Zhang, Zheyuan and Wang, Zehong and Ma, Tianyi and Taneja, Varun Sameer and Nelson, Sofia and Le, Nhi Ha Lan and Murugesan, Keerthiram and Ju, Mingxuan and Chawla, Nitesh V. and Zhang, Chuxu and Ye, Yanfang},
     booktitle = {Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
     year = {2025},
   }

9. ICML

   Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning

   Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, and Tong Zhao

   In Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025

   Bib HTML

   @inproceedings{bui2025hyperbolic,
     title = {Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning},
     author = {Bui, Ngoc and Yang, Menglin and Chen, Runjin and Neves, Leonardo and Ju, Mingxuan and Ying, Rex and Shah, Neil and Zhao, Tong},
     booktitle = {Proceedings of the 42nd International Conference on Machine Learning (ICML)},
     year = {2025},
   }

10. SIGIR

    Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat

    Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Ching Dou, Yang Zhou, Sohail Nizam, Rengim Ozturk, Yvette Liu, Sen Yang, Manish Malik, and Neil Shah

    In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2025

    arXiv Bib

    @inproceedings{ju2025userrep,
      title = {Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat},
      author = {Ju, Mingxuan and Neves, Leonardo and Kumar, Bhuvesh and Collins, Liam and Zhao, Tong and Qiu, Yuwei and Dou, Ching and Zhou, Yang and Nizam, Sohail and Ozturk, Rengim and Liu, Yvette and Yang, Sen and Malik, Manish and Shah, Neil},
      booktitle = {Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)},
      year = {2025},
    }

11. WWW

    GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems

    Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Mingxuan Ju, Neil Shah, and Tong Zhao

    In Proceedings of the ACM Web Conference (WWW), 2025

    arXiv Bib

    @inproceedings{wu2025graphhash,
      title = {GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems},
      author = {Wu, Xinyi and Loveland, Donald and Chen, Runjin and Liu, Yozen and Chen, Xin and Neves, Leonardo and Jadbabaie, Ali and Ju, Mingxuan and Shah, Neil and Zhao, Tong},
      booktitle = {Proceedings of the ACM Web Conference (WWW)},
      year = {2025},
    }

12. WWW

    Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank

    Donald Loveland, Xinyi Wu, Danai Koutra, Tong Zhao, Neil Shah, and Mingxuan Ju

    In Proceedings of the ACM Web Conference (WWW), 2025

    arXiv Bib

    @inproceedings{loveland2025matrixrank,
      title = {Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank},
      author = {Loveland, Donald and Wu, Xinyi and Koutra, Danai and Zhao, Tong and Shah, Neil and Ju, Mingxuan},
      booktitle = {Proceedings of the ACM Web Conference (WWW)},
      year = {2025},
    }

13. WWW-WS

    Improving Out-of-Vocabulary Handling in Recommendation Systems

    William Shiao, Mingxuan Ju, Zhichun Guo, Xin Chen, Evangelos Papalexakis, Tong Zhao, Neil Shah, and Yozen Liu

    In REL Workshop at the ACM Web Conference (WWW), 2025

    arXiv Bib

    @inproceedings{shiao2025oov,
      title = {Improving Out-of-Vocabulary Handling in Recommendation Systems},
      author = {Shiao, William and Ju, Mingxuan and Guo, Zhichun and Chen, Xin and Papalexakis, Evangelos and Zhao, Tong and Shah, Neil and Liu, Yozen},
      booktitle = {REL Workshop at the ACM Web Conference (WWW)},
      year = {2025},
    }

14. TMLR

    Node Duplication Improves Cold-start Link Prediction

    Zhichun Guo, Tong Zhao, Yozen Liu, Kaiwen Dong, William Shiao, Mingxuan Ju, Neil Shah, and Nitesh Chawla

    Transactions on Machine Learning Research (TMLR), 2025

    Bib HTML

    @article{guo2025nodedup,
      title = {Node Duplication Improves Cold-start Link Prediction},
      author = {Guo, Zhichun and Zhao, Tong and Liu, Yozen and Dong, Kaiwen and Shiao, William and Ju, Mingxuan and Shah, Neil and Chawla, Nitesh},
      journal = {Transactions on Machine Learning Research (TMLR)},
      year = {2025},
    }

2024

1. NeurIPS

   How Does Message Passing Improve Collaborative Filtering?

   Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, and Tong Zhao

   In Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS), 2024

   arXiv Bib Code

   @inproceedings{ju2024messagepassing,
     title = {How Does Message Passing Improve Collaborative Filtering?},
     author = {Ju, Mingxuan and Shiao, William and Guo, Zhichun and Ye, Yanfang and Liu, Yozen and Shah, Neil and Zhao, Tong},
     booktitle = {Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS)},
     year = {2024},
   }

2. ICML

   From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble

   Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, and Yanfang Ye

   In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024

   Bib HTML Code

   @inproceedings{wen2024mgse,
     title = {From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble},
     author = {Wen, Qianlong and Ju, Mingxuan and Ouyang, Zhongyu and Zhang, Chuxu and Ye, Yanfang},
     booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML)},
     year = {2024},
   }

3. RecSys-WS

   Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems

   Matthew Kolodner, Mingxuan Ju, Zihao Fan, Tong Zhao, Elham Ghazizadeh, Yan Wu, Neil Shah, and Yozen Liu

   In RobustRecSys Workshop at the ACM Conference on Recommender Systems (RecSys), 2024

   arXiv Bib

   @inproceedings{kolodner2024robust,
     title = {Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems},
     author = {Kolodner, Matthew and Ju, Mingxuan and Fan, Zihao and Zhao, Tong and Ghazizadeh, Elham and Wu, Yan and Shah, Neil and Liu, Yozen},
     booktitle = {RobustRecSys Workshop at the ACM Conference on Recommender Systems (RecSys)},
     year = {2024},
   }

4. arXiv

   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, and Tong Zhao

   arXiv preprint, 2024

   arXiv Bib

   @article{chen2024tokenization,
     title = {Enhancing Item Tokenization for Generative Recommendation through Self-Improvement},
     author = {Chen, Runjin and Ju, Mingxuan and Bui, Ngoc and Antypas, Dimosthenis and Cai, Stanley and Wu, Xiaopeng and Neves, Leonardo and Wang, Zhangyang and Shah, Neil and Zhao, Tong},
     journal = {arXiv preprint},
     year = {2024},
   }

2023

1. NeurIPS

   GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation

   Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, and Yanfang Ye

   In Proceedings of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS), 2023

   arXiv Bib PDF Code

   @inproceedings{ju2023graphpatcher,
     title = {GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation},
     author = {Ju, Mingxuan and Zhao, Tong and Yu, Wenhao and Shah, Neil and Ye, Yanfang},
     booktitle = {Proceedings of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS)},
     year = {2023},
   }

2. ICLR

   Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization

   Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, and Chuxu Zhang

   In Proceedings of the 11th International Conference on Learning Representations (ICLR), 2023

   Bib HTML Code

   @inproceedings{ju2023paretognn,
     title = {Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization},
     author = {Ju, Mingxuan and Zhao, Tong and Wen, Qianlong and Yu, Wenhao and Shah, Neil and Ye, Yanfang and Zhang, Chuxu},
     booktitle = {Proceedings of the 11th International Conference on Learning Representations (ICLR)},
     year = {2023},
   }

3. ICLR

   Generate rather than Retrieve: Large Language Models are Strong Context Generators

   Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chengguang Zhu, Michael Zeng, and Meng Jiang

   In Proceedings of the 11th International Conference on Learning Representations (ICLR), 2023

   Bib HTML

   @inproceedings{yu2023genread,
     title = {Generate rather than Retrieve: Large Language Models are Strong Context Generators},
     author = {Yu, Wenhao and Iter, Dan and Wang, Shuohang and Xu, Yichong and Ju, Mingxuan and Sanyal, Soumya and Zhu, Chengguang and Zeng, Michael and Jiang, Meng},
     booktitle = {Proceedings of the 11th International Conference on Learning Representations (ICLR)},
     year = {2023},
   }

4. ICLR

   Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization

   Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, and Chuxu Zhang

   In Proceedings of the 11th International Conference on Learning Representations (ICLR), 2023

   Bib HTML

   @inproceedings{zhang2023robustness,
     title = {Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization},
     author = {Zhang, Chunhui and Tian, Yijun and Ju, Mingxuan and Liu, Zheyuan and Ye, Yanfang and Chawla, Nitesh and Zhang, Chuxu},
     booktitle = {Proceedings of the 11th International Conference on Learning Representations (ICLR)},
     year = {2023},
   }

5. AAAI

   Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning

   Mingxuan Ju, Yujie Fan, Chuxu Zhang, and Yanfang Ye

   In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023

   arXiv Bib Code

   @inproceedings{ju2023goboard,
     title = {Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning},
     author = {Ju, Mingxuan and Fan, Yujie and Zhang, Chuxu and Ye, Yanfang},
     booktitle = {Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI)},
     year = {2023},
   }

6. WSDM

   Self-Supervised Graph Structure Refinement for Graph Neural Networks

   Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, and Yanfang Ye

   In Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM), 2023

   arXiv Bib Code

   @inproceedings{zhao2023gsr,
     title = {Self-Supervised Graph Structure Refinement for Graph Neural Networks},
     author = {Zhao, Jianan and Wen, Qianlong and Ju, Mingxuan and Zhang, Chuxu and Ye, Yanfang},
     booktitle = {Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM)},
     year = {2023},
   }

7. ECIR

   Leveraging Comment Retrieval for Code Summarization

   Shifu Hou, Lingwei Chen, Mingxuan Ju, and Yanfang Ye

   In Proceedings of the 45th European Conference on Information Retrieval (ECIR), 2023

   Bib HTML

   @inproceedings{hou2023comment,
     title = {Leveraging Comment Retrieval for Code Summarization},
     author = {Hou, Shifu and Chen, Lingwei and Ju, Mingxuan and Ye, Yanfang},
     booktitle = {Proceedings of the 45th European Conference on Information Retrieval (ECIR)},
     year = {2023},
   }

8. TACL

   Exploring Contrast Consistency of Open-domain Question Answering Systems on Minimally Edited Questions

   Zhihan Zhang, Wenhao Yu, Zheng Ning, Mingxuan Ju, and Meng Jiang

   Transactions of the Association for Computational Linguistics (TACL), 2023

   arXiv Bib Code

   @article{zhang2023contrast,
     title = {Exploring Contrast Consistency of Open-domain Question Answering Systems on Minimally Edited Questions},
     author = {Zhang, Zhihan and Yu, Wenhao and Ning, Zheng and Ju, Mingxuan and Jiang, Meng},
     journal = {Transactions of the Association for Computational Linguistics (TACL)},
     year = {2023},
   }

2022

1. EMNLP

   Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering

   Mingxuan Ju^*, Wenhao Yu^*, Tong Zhao, Chuxu Zhang, and Yanfang Ye

   In Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

   arXiv Bib Code

   @inproceedings{ju2022grape,
     title = {Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering},
     author = {Ju, Mingxuan and Yu, Wenhao and Zhao, Tong and Zhang, Chuxu and Ye, Yanfang},
     booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2022},
     year = {2022},
   }

2. SDM

   Heterogeneous Temporal Graph Neural Network

   Yujie Fan, Mingxuan Ju, Chuxu Zhang, Liang Zhao, and Yanfang Ye

   In Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), 2022

   Bib HTML Code

   @inproceedings{fan2022htgnn,
     title = {Heterogeneous Temporal Graph Neural Network},
     author = {Fan, Yujie and Ju, Mingxuan and Zhang, Chuxu and Zhao, Liang and Ye, Yanfang},
     booktitle = {Proceedings of the 2022 SIAM International Conference on Data Mining (SDM)},
     year = {2022},
   }

3. AAAI

   Adaptive Kernel Graph Neural Network

   Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Liang Zhao, and Yanfang Ye

   In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022

   Bib PDF Code

   @inproceedings{ju2022akgnn,
     title = {Adaptive Kernel Graph Neural Network},
     author = {Ju, Mingxuan and Hou, Shifu and Fan, Yujie and Zhao, Jianan and Zhao, Liang and Ye, Yanfang},
     booktitle = {Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI)},
     year = {2022},
   }

2021

1. WWW

   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, Yujie Fan, Shifu Hou, Kenneth Loparo, and Liang Zhao

   In Proceedings of the Web Conference (WWW), 2021

   Best Paper Shortlist Bib HTML Code

   Best Paper Award Shortlist at WWW 2021

   @inproceedings{ju2021dremotion,
     title = {Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond},
     author = {Ju, Mingxuan and Song, Wei and Sun, Shiyu and Ye, Yanfang and Fan, Yujie and Hou, Shifu and Loparo, Kenneth and Zhao, Liang},
     booktitle = {Proceedings of the Web Conference (WWW)},
     year = {2021},
   }

2. KDD

   Heterogeneous Temporal Graph Transformer: An Intelligent System for Evolving Android Malware Detection

   Yujie Fan, Mingxuan Ju, Shifu Hou, Yanfang Ye, Wenqiang Wan, Kui Wang, Yinming Mei, and Qi Xiong

   In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Applied Data Science Track, 2021

   Bib HTML

   @inproceedings{fan2021htgt,
     title = {Heterogeneous Temporal Graph Transformer: An Intelligent System for Evolving Android Malware Detection},
     author = {Fan, Yujie and Ju, Mingxuan and Hou, Shifu and Ye, Yanfang and Wan, Wenqiang and Wang, Kui and Mei, Yinming and Xiong, Qi},
     booktitle = {Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Applied Data Science Track},
     year = {2021},
   }

3. AAAI

   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, Wenqiang Wan, Kui Wang, Yinming Mei, Qi Xiong, and Fudong Shao

   In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021

   Bib HTML

   @inproceedings{hou2021disentangled,
     title = {Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond},
     author = {Hou, Shifu and Fan, Yujie and Ju, Mingxuan and Ye, Yanfang and Wan, Wenqiang and Wang, Kui and Mei, Yinming and Xiong, Qi and Shao, Fudong},
     booktitle = {Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI)},
     year = {2021},
   }

4. CIKM

   Community Mitigation: A Data-driven System for COVID-19 Risk Assessment in a Hierarchical Manner

   Yanfang Ye, Yujie Fan, Shifu Hou, Yiming Zhang, Yiyue Qian, Shiyu Sun, Qian Peng, Mingxuan Ju, Wei Song, and Kenneth Loparo

   In Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 2021

   Bib HTML

   @inproceedings{ye2021community,
     title = {Community Mitigation: A Data-driven System for COVID-19 Risk Assessment in a Hierarchical Manner},
     author = {Ye, Yanfang and Fan, Yujie and Hou, Shifu and Zhang, Yiming and Qian, Yiyue and Sun, Shiyu and Peng, Qian and Ju, Mingxuan and Song, Wei and Loparo, Kenneth},
     booktitle = {Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM)},
     year = {2021},
   }

2020

1. JBHI

   a-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States

   Yanfang Ye, Yujie Fan, Shifu Hou, Yiming Zhang, Yiyue Qian, Shiyu Sun, Qian Peng, Mingxuan Ju, Wei Song, and Kenneth Loparo

   IEEE Journal of Biomedical and Health Informatics (JBHI), 2020

   Bib HTML

   @article{ye2020asatellite,
     title = {a-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States},
     author = {Ye, Yanfang and Fan, Yujie and Hou, Shifu and Zhang, Yiming and Qian, Yiyue and Sun, Shiyu and Peng, Qian and Ju, Mingxuan and Song, Wei and Loparo, Kenneth},
     journal = {IEEE Journal of Biomedical and Health Informatics (JBHI)},
     year = {2020},
   }

2019

1. ObGyn

   Development and Validation of a Machine Learning Algorithm for Predicting Response to Anticholinergic Medications for Overactive Bladder Syndrome

   David Sheyn, Mingxuan Ju, Sixiao Zhang, Caleb Anyaeche, Adonis Hijaz, Jeffrey Mangel, Sangeeta Mahajan, Britt Conroy, Sherif El-Nashar, and Soumya Ray

   Obstetrics & Gynecology, 2019

   Bib HTML

   @article{sheyn2019anticholinergic,
     title = {Development and Validation of a Machine Learning Algorithm for Predicting Response to Anticholinergic Medications for Overactive Bladder Syndrome},
     author = {Sheyn, David and Ju, Mingxuan and Zhang, Sixiao and Anyaeche, Caleb and Hijaz, Adonis and Mangel, Jeffrey and Mahajan, Sangeeta and Conroy, Britt and El-Nashar, Sherif and Ray, Soumya},
     journal = {Obstetrics \& Gynecology},
     year = {2019},
   }

2018

1. BigData

   A Multi-representation Ensemble Approach to Classifying Vocal Diseases

   Mingxuan Ju, Zhengkai Jiang, Yufan Chen, and Soumya Ray

   In Proceedings of the 2018 IEEE International Conference on Big Data (BigData), 2018

   FEMH Cup 3rd Place Bib HTML Code

   3rd Place Award at the IEEE Big Data 2018 FEMH Challenge

   @inproceedings{ju2018vocal,
     title = {A Multi-representation Ensemble Approach to Classifying Vocal Diseases},
     author = {Ju, Mingxuan and Jiang, Zhengkai and Chen, Yufan and Ray, Soumya},
     booktitle = {Proceedings of the 2018 IEEE International Conference on Big Data (BigData)},
     year = {2018},
   }