World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
6334
World Ranking
9777
National Ranking
4124

Overview

Xuanhui Wang is a researcher primarily affiliated with Google in the United States. Their scholarly work is rooted in the field of Computer Science, with a strong focus on Artificial Intelligence. Other areas of specialization include Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research, and Ocean Engineering.

Their research covers a range of topics including:

  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Natural Language Processing Techniques
  • Machine Learning and Data Classification
  • Imbalanced Data Classification Techniques
  • Machine Learning and Algorithms
  • Rock Mechanics and Modeling

Their recent publications include:

  • "An improved Faster R-CNN model for multi-object tomato maturity detection in complex scenarios," 2022, Ecological Informatics
  • "Learning-to-Rank with BERT in TF-Ranking," 2020, arXiv (Cornell University)
  • "Effects of moisture conditions on mechanical properties and AE and IR characteristics in coal-rock combinations," 2020, Arabian Journal of Geosciences
  • "Experimental Study of Coal Sample Damage in Acidic Water Environments," 2021, Mine Water and the Environment
  • "Revisiting Two-tower Models for Unbiased Learning to Rank," 2022, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Xuanhui Wang frequently collaborates with other researchers, with prominent coauthors including Michael Bendersky, Honglei Zhuang, Marc Najork, Zhen Qin, and Rolf Jagerman.

Their publications often appear in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • Ecological Informatics
  • Arabian Journal of Geosciences

Best Publications

  • Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms

    Lihong Li;Wei Chu;John Langford;Xuanhui Wang

  • Have things changed now?: an empirical study of bug characteristics in modern open source software

    Zhenmin Li;Lin Tan;Xuanhui Wang;Shan Lu

  • Learning to Rank with Selection Bias in Personal Search

    Xuanhui Wang;Michael Bendersky;Donald Metzler;Marc Najork

  • Position Bias Estimation for Unbiased Learning to Rank in Personal Search

    Xuanhui Wang;Nadav Golbandi;Michael Bendersky;Donald Metzler

  • Mining correlated bursty topic patterns from coordinated text streams

    Xuanhui Wang;ChengXiang Zhai;Xiao Hu;Richard Sproat

  • Learn from web search logs to organize search results

    Xuanhui Wang;ChengXiang Zhai

  • Bug characteristics in open source software

    Lin Tan;Chen Liu;Zhenmin Li;Xuanhui Wang

  • Locality preserving nonnegative matrix factorization

    Deng Cai;Xiaofei He;Xuanhui Wang;Hujun Bao

  • Probabilistic dyadic data analysis with local and global consistency

    Deng Cai;Xuanhui Wang;Xiaofei He

  • Mining term association patterns from search logs for effective query reformulation

    Xuanhui Wang;ChengXiang Zhai

  • Language Model Information Retrieval with Document Expansion

    Tao Tao;Xuanhui Wang;Qiaozhu Mei;ChengXiang Zhai

  • A study of methods for negative relevance feedback

    Xuanhui Wang;Hui Fang;ChengXiang Zhai

  • Detect and track latent factors with online nonnegative matrix factorization

    Bin Cao;Dou Shen;Jian-Tao Sun;Xuanhui Wang

  • Estimating Position Bias without Intrusive Interventions

    Aman Agarwal;Ivan Zaitsev;Xuanhui Wang;Cheng Li

  • The LambdaLoss Framework for Ranking Metric Optimization

    Xuanhui Wang;Cheng Li;Nadav Golbandi;Michael Bendersky

  • TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank

    Rama Kumar Pasumarthi;Sebastian Bruch;Xuanhui Wang;Cheng Li

  • Learning to model relatedness for news recommendation

    Yuanhua Lv;Taesup Moon;Pranam Kolari;Zhaohui Zheng

  • Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks

    Qingyao Ai;Xuanhui Wang;Sebastian Bruch;Nadav Golbandi

  • CBC: clustering based text classification requiring minimal labeled data

    Hua-Jun Zeng;Xuan-Hui Wang;Zheng Chen;Hongjun Lu

  • RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses

    Unknown

  • Clustering based text classification

    Hua-Jun Zeng;Xuanhui Wang;Zheng Chen;Benyu Zhang

  • Learning-to-Rank with BERT in TF-Ranking

    Shuguang Han;Xuanhui Wang;Mike Bendersky;Marc Najork

Frequent Co-Authors

Michael Bendersky
Michael Bendersky Google (United States)
Marc Najork
Marc Najork Google (United States)
Donald Metzler
Donald Metzler Google (United States)
ChengXiang Zhai
ChengXiang Zhai University of Illinois at Urbana-Champaign
Zheng Chen
Zheng Chen Microsoft Research Asia (China)
Jian-Tao Sun
Jian-Tao Sun Microsoft (United States)
Hua-Jun Zeng
Hua-Jun Zeng Rulai, Inc.
Yi Chang
Yi Chang Jilin University
John Langford
John Langford Microsoft (United States)
Lihong Li
Lihong Li Amazon (United States)

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