World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
8863
World Ranking
7166
National Ranking
948

Overview

Yaliang Li is affiliated with Alibaba Group in China and specializes in the field of computer science, with a focus on artificial intelligence and related subfields. Their research contributions span a range of areas including advanced graph neural networks, privacy-preserving technologies in data, recommender systems and techniques, natural language processing techniques, and cryptography and data security.

The scientist has published extensively, with 271 publications primarily in computer science. Among these, artificial intelligence constitutes a significant portion with 206 publications. Other subfields covered include information systems, computer vision and pattern recognition, management science and operations research, and computer networks and communications.

Yaliang Li's frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the VLDB Endowment
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • ACM Transactions on Information Systems

Recent notable papers authored or co-authored by Yaliang Li include:

  • "Simple and Deep Graph Convolutional Networks," 2020, arXiv (Cornell University)
  • "A Survey on Causal Inference," 2021, ACM Transactions on Knowledge Discovery from Data
  • "Towards Universal Sequence Representation Learning for Recommender Systems," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • "Modeling Relation Paths for Knowledge Graph Completion," 2020, IEEE Transactions on Knowledge and Data Engineering
  • "Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation," 2024, Proceedings of the VLDB Endowment

The scientist frequently collaborates with other researchers including Bolin Ding, Yuexiang Xie, Daoyuan Chen, Jingren Zhou, and Wayne Xin Zhao.

Main research topics pursued by Yaliang Li encompass:

  • Topic Modeling
  • Privacy-Preserving Technologies in Data
  • Advanced Graph Neural Networks
  • Recommender Systems and Techniques
  • Natural Language Processing Techniques
  • Cryptography and Data Security
  • Stochastic Gradient Optimization Techniques

Best Publications

  • Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation

    Qi Li;Yaliang Li;Jing Gao;Bo Zhao

  • A Survey on Truth Discovery

    Yaliang Li;Jing Gao;Chuishi Meng;Qi Li

  • Simple and Deep Graph Convolutional Networks

    Ming Chen;Zhewei Wei;Zengfeng Huang;Bolin Ding

  • A Survey on Causal Inference

    Liuyi Yao;Zhixuan Chu;Sheng Li;Yaliang Li

  • A confidence-aware approach for truth discovery on long-tail data

    Qi Li;Yaliang Li;Jing Gao;Lu Su

  • RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms

    Wayne Xin Zhao;Shanlei Mu;Yupeng Hou;Zihan Lin

  • Towards Universal Sequence Representation Learning for Recommender Systems

    Unknown

  • Joint Slot Filling and Intent Detection via Capsule Neural Networks

    Chenwei Zhang;Yaliang Li;Nan Du;Wei Fan

  • FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation

    Fenglong Ma;Yaliang Li;Qi Li;Minghui Qiu

  • On the Discovery of Evolving Truth

    Yaliang Li;Qi Li;Jing Gao;Lu Su

  • Cloud-Enabled Privacy-Preserving Truth Discovery in Crowd Sensing Systems

    Chenglin Miao;Wenjun Jiang;Lu Su;Yaliang Li

  • Truth Discovery on Crowd Sensing of Correlated Entities

    Chuishi Meng;Wenjun Jiang;Yaliang Li;Jing Gao

  • Representation Learning for Treatment Effect Estimation from Observational Data

    Liuyi Yao;Sheng Li;Yaliang Li;Mengdi Huai

  • Crowdsourcing for multiple-choice question answering

    Bahadir Ismail Aydin;Yavuz Selim Yilmaz;Yaliang Li;Qi Li

  • Modeling Relation Paths for Knowledge Graph Completion

    Ying Shen;Ning Ding;Hai-Tao Zheng;Yaliang Li

  • Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

    Unknown

  • Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning

    Yang Deng;Yaliang Li;Fei Sun;Bolin Ding

  • Conflicts to Harmony: A Framework for Resolving Conflicts in Heterogeneous Data by Truth Discovery

    Yaliang Li;Qi Li;Jing Gao;Lu Su

  • A lightweight privacy-preserving truth discovery framework for mobile crowd sensing systems

    Chenglin Miao;Lu Su;Wenjun Jiang;Yaliang Li

  • FederatedScope: A Flexible Federated Learning Platform for Heterogeneity

    Unknown

  • A Correlated Topic Model Using Word Embeddings

    Guangxu Xun;Yaliang Li;Wayne Xin Zhao;Jing Gao

  • Scalable Graph Neural Networks via Bidirectional Propagation

    Ming Chen;Zhewei Wei;Bolin Ding;Yaliang Li

  • RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms

    Wayne Xin Zhao;Shanlei Mu;Yupeng Hou;Zihan Lin

Frequent Co-Authors

Jing Gao
Jing Gao Purdue University West Lafayette
Nan Du
Nan Du Tencent (China)
Wei Fan
Wei Fan Tencent (China)
Ying Shen
Ying Shen Sun Yat-sen University
Lu Su
Lu Su Purdue University West Lafayette
Aidong Zhang
Aidong Zhang University of Virginia
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Wayne Xin Zhao
Wayne Xin Zhao Renmin University of China
Jingren Zhou
Jingren Zhou Alibaba Group (China)
Sheng Li
Sheng Li University of Virginia

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