Publications

Preprints

• Shitao Xiao, Zheng Liu, Yingxia Shao, Defu Lian, Shengluan Hou, Zhao Cao. ColBERT-Lite: High-Fidelity Light-Weighting of Late Interaction Retrievers Via Differentiable Vector Quantization.
• Hongjin Qian, Yutao Zhu, Zhicheng Dou, Haoqi Gu, Xinyu Zhang, Zheng Liu, Ruofei Lai, Zhao Cao, Jian-Yun Nie, Ji-Rong Wen. WebBrain: Learning to Generate Factually Correct Articles for Queries by Grounding on Large Web Corpus (Media Coverage in Chinese).
• Shitao Xiao, Zheng Liu, RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models. (Codebase, SOTA pre-trained model on MSMARCO and BEIR benchmark).
• Peitian Zhang, Zheng Liu. Bi-Phase Enhanced IVFPQ for Time-Efficient Ad-hoc Retrieval. (Codebase)

2023

• [ACL] Shitao Xiao, Zheng Liu, Yingxia Shao, Zhao Cao, RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models. In Proceedings of The 61st Annual Meeting of the Association for Computational Linguistics (ACL’23).
• [SIGIR] Chaofan Li, Zheng Liu, Shitao Xiao, Yingxia Shao, Defu Lian, Zhao Cao. LibVQ: A Toolkit For Optimizing Vector Quantization And Efficient Neural Retrieval. (Codebase, Demo). System demonstration in SIGIR 2023.
• [SIGIR] Defu Lian, Xu Huang, Xiaolong Chen, Jin Chen, Yankai Wang, Haoran Jin, Rui Fan, Xingmei Wang, Zheng Liu, Le Wu and Enhong Chen. RecStudio: Towards a Highly-Modularized Recommender System. Codebase. Resource paper in SIGIR 2023.
• [SIGIR] Haitao Li, Qingyao Ai, Jiaxin Mao, Yiqun Liu, Zheng Liu, Zhao Cao. Constructing Tree-based Index for Efficient and Effective Dense Retrieval, In Proceedings of SIGIR 2023.
• [WWW] Xu Huang, Defu Lian, Jin Chen, Liu Zheng, Xing Xie and Enhong Chen. Cooperative Retriever and Ranker in Deep Recommenders. In Proceedings of the Web Conference 2023.
• [DASFAA] Wenqi Sun, Xinyan Fan, Zheng Liu, Ji-Rong Wen, Wayne Xin Zhao. Towards Efficient and Effective Transformers for Sequential Recommendation. In Proceedings of the 28th International Conference on Database Systems for Advanced Applications.
• [TKDE] Chaozhuo Li, Senzhang Wang, Zheng Liu, Xing Xie, Lei Chen, Philip S. Yu. Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-Learning. Accepted to IEEE Transactions on Knowledge and Data Engineering.
• [TOIS] Yiqi Wang, Chaozhuo Li, Zheng Liu, Mingzheng Li, Jiliang Tang, Xing Xie, Lei Chen, Philip S. Yu. An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering. Accepted to ACM Transactions on Information Systems.
• [TIST] Jing Yao, Zheng Liu, Junhan Yang, Zhicheng Dou, Xing Xie, Ji-Rong Wen. CDSM: Cascaded Deep Semantic Matching on Textual Graphs Leveraging Ad-hoc Neighbor Selection. Accepted to ACM Transactions on Intelligent Systems and Technology.

2022

• [EMNLP] Shitao Xiao, Zheng Liu, Yingxia Shao, Zhao Cao, RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing.
• [NeurIPS] Chao Feng, Wuchao Li, Defu Lian, Zheng Liu, Enhong Chen. Recommender Forest for Efficient Retrieval. In Advances in Neural Information Processing Systems 35 (NeurIPS 2022).
• [NeurIPS] Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Allen Sun, Weiwei Deng, Qi Zhang, Mao Yang. A Neural Corpus Indexer for Document Retrieval. In Advances in Neural Information Processing Systems 35 (NeurIPS 2022). (Outstanding Paper Award)
• [KDD] Jianjin Zhang, Zheng Liu, Weihao Han, Shitao Xiao, Ruicheng Zheng, Yingxia Shao, Hao Sun, Premkumar Srinivasan, Weiwei Deng, Qi Zhang, Xing Xie. Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining.
• [KDD] Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Fangzhao Wu, Bhuvan Middha, Xing Xie, Training Large-Scale News Recommenders with Pretrained Language Models in the Loop. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining.
• [SIGIR] Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao and Xing Xie. Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
• [SIGIR] Chao Feng, Defu Lian, Zheng Liu, Xing Xie, Le Wu and Enhong Chen. Forest-based Deep Recommende. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
• [SIGIR] Xinyan Fan, Jianxun Lian, Wayne Xin Zhao, Zheng Liu, Chaozhuo Li and Xing Xie. Ada-Ranker: A Data Distribution Adaptive Ranking Paradigm for Sequential Recommendation. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
• [WWW] Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Chaozhuo Li, Yingxia Shao, Defu Lian, Hao Sun, Denvy Deng, Liangjie Zhang, Qi Zhang, Xing Xie. Progressively OPtimized Bi-Granular Document Representation for Scale Embedding Based Retrieval. In Proceedings of The Web Conference 2022.
• [WWW] Xufang Luo, Zheng Liu, Shitao Xiao, Xing Xie, Dongsheng Li. MINDSim: User Simulator for News Recommenders. In Proceedings of The Web Conference 2022.
• [COLING] Zhaoye Fei, Yu Tian, Yongkang Wu, Xinyu Zhang, Yutao Zhu, Zheng Liu, Jiawen Wu, Dejiang Kong, Ruofei Lai, Zhao Cao, Zhicheng Dou, Xipeng Qiu. Coarse-to-Fine: Hierarchical Multi-task Learning for Natural Language Understanding. In Proceedings of the 29th International Conference on Computational Linguistics.
• [AAAI] Jin Zhang, Qi Liu, Defu Lian, Zheng Liu, Le Wu, Enhong Chen. Anisotropic Additive Quantization for Fast Inner Product Search. In Proceedings of the AAAI Conference on Artificial Intelligence, 36(4), 4354-4362.
• [TOIS] Chao Feng , Defu Lian , Xiting Wang , Zheng Liu , Xing Xie , Enhong Chen. Reinforcement Routing on Proximity Graph for Efficient Recommendation. In ACM Transactions on Information Systems.

2021

• [EMNLP] Shitao Xiao, Zheng Liu, Yingxia Shao, Defu Lian, Xing Xie. Matching-oriented Product Quantization For Ad-hoc Retrieval. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
• [EMNLP] Shuxian Bi, Chaozhuo Li, Xiao Han, Zheng Liu, Xing Xie, Haizhen Huang and Zengxuan Wen. Leveraging Bidding Graphs for Advertiser-Aware Relevance Modeling in Sponsored Search. In Findings of the Association for Computational Linguistics: EMNLP 2021.
• [NeurIPS] Junhan Yang, Zheng Liu, Shitao Xiao, Chaozhuo Li, Defu Lian, Sanjay Agrawal, Amit Singh, Guangzhong Sun, Xing Xie. GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph. In Advances in Neural Information Processing Systems 34 (NeurIPS 2021).
• [KDD] Danyang Liu, Jianxun Lian, Zheng Liu, Xiting Wang, Guangzhong Sun, Xing Xie. Reinforced Anchor Knowledge Graph Generation for News Recommendation Reasoning. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining.
• [SIGIR] Xinyan Fan, Zheng Liu, Jianxun Lian, Wayne Xin Zhao, Xing Xie, Ji-Rong Wen. Lighter and Better: Low-Rank Decomposed Self-Attention Networks for Next-Item Recommendation. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval.
• [SIGIR] Chaozhuo Li, Bochen Pang, Yuming Liu, Hao Sun, Zheng Liu, Xing Xie, Tianqi Yang, Yanling Cui, Liangjie Zhang, Qi Zhang, AdsGNN: Behavior-Graph Augmented Relevance Modeling in Sponsored Search. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in. Information Retrieval.

2020

• [NeurIPS] Binbin Jin, Defu Lian, Zheng Liu, Qi Liu, Jianhui Ma, Xing Xie, Enhong Chen. Sampling-Decomposable Generative Adversarial Recommender. In Advances in Neural Information Processing Systems 33 (NeurIPS 2020).
• [SIGIR] Zheng Liu, Jianxun Lian, Junhan Yang, Defu Lian, Xing Xie. Octopus: Comprehensive and Elastic User Representation for the Generation of Recommendation Candidates. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.
• [SIGIR] Kangzhi Zhao, Xiting Wang, Yuren Zhang, Li Zhao, Zheng Liu, Chunxiao Xing, Xing Xie. Leveraging demonstrations for reinforcement recommendation reasoning over knowledge graphs. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.
• [WWW] Defu Lian, Haoyu Wang, Zheng Liu, Jianxun Lian, Enhong Chen, Xing Xie. Lightrec: A memory and search-efficient recommender system. In Proceedings of The Web Conference 2020.
• [ACL] Heyuan Wang, Fangzhao Wu, Zheng Liu, Xing Xie. Fine-grained interest matching for neural news recommendation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.

2019

• [IJCAI] Zheng Liu, Yu Xing, Fangzhao Wu, Mingxiao An, Xing Xie. Hi-Fi Ark: Deep User Representation via High-Fidelity Archive Network. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence.
• [ACL] Mingxiao An, Fangzhao Wu, Chuhan Wu, Kun Zhang, Zheng Liu, Xing Xie. Neural news recommendation with long-and short-term user representations. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.

Before 2019

• [KDD] Zheng Liu, Xing Xie, Lei Chen. Context-aware academic collaborator recommendation. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.
• [VLDB] Zheng Liu, Lei Chen. Worker recommendation for crowdsourced q&a services: A triple-factor aware approach. In Proceedings of the VLDB Endowment.
• [ICDE] Zheng Liu, Lei Chen, Yongxin Tong. Realtime traffic speed estimation with sparse crowdsourced data. In 2018 IEEE 34th International Conference on Data Engineering (ICDE).
• [ICDE] Chen Cao, Jiayang Tu, Zheng Liu, Lei Chen, HV Jagadish. Tuning crowdsourced human computation. In 2017 IEEE 33rd International Conference on Data Engineering (ICDE).
• [ICDE] Zheng Liu, Lei Chen. Mutual benefit aware task assignment in a bipartite labor market. In 2016 IEEE 32nd International Conference on Data Engineering (ICDE).
• [ICDE] Chen Jason Zhang, Lei Chen, Yongxin Tong, Zheng Liu. Cleaning uncertain data with a noisy crowd. In 2015 IEEE 31st International Conference on Data Engineering.
• [VLDB] Zhao Chen, Rui Fu, Ziyuan Zhao, Zheng Liu, Leihao Xia, Lei Chen, Peng Cheng, Caleb Chen Cao, Yongxin Tong, Chen Jason Zhang. gmission: A general spatial crowdsourcing platform. In Proceedings of the VLDB Endowment. (VLDB 2014 Excellent Demonstration Award)