Jingyue Gao

Jingyue Gao 高敬月

Douyin Search ByteDance

I lead the R&D team of retrieval and query understanding (召回&Query理解) for Douyin Search (抖音搜索) at ByteDance.

My current focus is on applying large language models (LLMs) to contextualized query understanding, retrieval, and ranking in large-scale industrial systems.

Experience

  • 2023 - Present

    ByteDance

    Douyin Search

  • 2021 - 2023

    Alibaba

    Alimama Display Advertising

Education

  • 2018 - 2021

    Peking University

    M.S. in Computer Science
    Advised by Prof. Yasha Wang

  • 2014 - 2018

    Peking University

    B.S. in Computer Science

Earlier internships (4)
  • Jun - Sep 2020

    Alibaba

    Machine learning engineering intern; unbiased ranking models.

  • Jun - Sep 2019

    Google, Mountain View

    Software engineering intern; intelligence layer of Fuchsia.

  • Sep 2017 - Jul 2018

    MSRA

    Research intern; explainable recommendation models.

  • Apr - Jun 2017

    DiDi

    Software engineering intern; large-scale feature management for machine learning.

Publications

  1. LEMUR: Large scale End-to-end MUltimodal Recommendation

    CIKM 2026 Paper
    Full author list (including Jingyue Gao*)

    Xintian Han*, Honggang Chen*, Quan Lin*, Jingyue Gao*, Xiangyuan Ren*, Lifei Zhu, Zhisheng Ye, Shikang Wu, XiongHang Xie, Xiaochu Gan, Bingzheng Wei, Peng Xu, Zhe Wang, Yuchao Zheng, Jingjian Lin, Di Wu, Junfeng Ge.

    * Equal contribution.

  2. Rec4Ad: A Free Lunch to Mitigate Sample Selection Bias for Ads CTR Prediction in Taobao

    CIKM 2023 Paper

    Jingyue Gao, Shuguang Han, Han Zhu, Siran Yang, Yuning Jiang, Jian Xu, Bo Zheng.

  3. COPR: Consistency-Oriented Pre-Ranking for Online Advertising

    CIKM 2023 Paper

    Jingyue Gao*, Zhishan Zhao*, Yu Zhang, Shuguang Han, Siyuan Lou, Xiang-Rong Sheng, Zhe Wang, Han Zhu, Yuning Jiang, Jian Xu, Bo Zheng.

    * Equal contribution.

  4. Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model

    SIGKDD 2023 Paper

    Xiang-Rong Sheng, Jingyue Gao, Yueyao Cheng, Siran Yang, Shuguang Han, Hongbo Deng, Yuning Jiang, Jian Xu, Bo Zheng.

  5. Learning Groupwise Explanations for Black-Box Models

    IJCAI 2021

    Jingyue Gao, Xiting Wang, Yasha Wang, Yulan Yan, Xing Xie.

  6. U-BERT: Pre-Training User Representations for Improved Recommendation

    AAAI 2021

    Zhaopeng Qiu, Xian Wu, Jingyue Gao, Wei Fan.

  7. Set-Sequence-Graph: A Multi-View Approach Towards Exploiting Reviews for Recommendation

    CIKM 2020 Paper Code

    Jingyue Gao, Yang Lin, Yasha Wang, Xiting Wang, Zhao Yang, Yuanduo He, Xu Chu.

  8. Explainable Recommendation Through Attentive Multi-View Learning

    AAAI 2019 Paper

    Jingyue Gao, Xiting Wang, Yasha Wang, Xing Xie.

  9. STAR: Spatio-Temporal Taxonomy-Aware Tag Recommendation for Citizen Complaints

    CIKM 2019 Paper Code

    Jingyue Gao*, Yuanduo He*, Yasha Wang, Xiting Wang, Jiangtao Wang, Guangju Peng, Xu Chu.

    * Equal contribution.

  10. CAMP: Co-Attention Memory Networks for Diagnosis Prediction in Healthcare

    ICDM 2019 Paper Code

    Jingyue Gao, Xiting Wang, Yasha Wang, Zhao Yang, Junyi Gao, Jiangtao Wang, Wen Tang, Xing Xie.

  11. MuLDA: A Multi-Task Semi-Supervised Learning Framework for Drug-Drug Interaction Prediction

    IJCAI 2019 Paper

    Xu Chu, Yang Lin, Yasha Wang, Leye Wang, Jiangtao Wang, Jingyue Gao.

  12. CAPED: Context-Aware Powerlet-Based Energy Disaggregation

    PAKDD 2018 Paper

    Jingyue Gao, Yasha Wang, Xu Chu, Yuanduo He, Ziqing Mao.