About me

Hi! My name is Yuchen Li. I am currently a senior researcher at Baidu Search Science, collaborating closely with Dr. Dawei Yin, Dr. Shuaiqiang Wang and Dr. Rui Kong. I am also an adjunct researcher in Intelligent Network and Trusted Computing Laboratory at Shanghai Jiao Tong University, collaborating with Prof. Linghe Kong (IEEE Fellow, Changjiang Distinguished Professor). I received my Ph.D. degree from the Department of Computer Science and Engineering at Shanghai Jiao Tong University in June 2024, under the supervision of Prof. Linghe Kong (IEEE Fellow, Changjiang Distinguished Professor) and Prof. Guihai Chen (IEEE Fellow, NSFC Distinguished Young Scholar). From 2021 until my graduation, I served as a research intern in Big Data Laboratory at Baidu Inc., under the mentorship of Dr. Haoyi Xiong and Prof. Dejing Dou, working closely with Dr. Dawei Yin and Dr. Shuaiqiang Wang. I have published research papers in premium conferences and journals, and have been the recipient of three best paper awards or nominations, including ICDM, DSAA and PRICAI.
Research Interests:
My research focuses on data-driven intelligent computing for interconnected systems, with an emphasis on the training and inference of Large Language Models (LLMs). On the training side, I work on optimizing attention mechanisms and Mixture-of-Experts (MoE) architectures during pre-training, as well as developing post-training techniques for AI agents. On the inference side, I focus on speculative sampling, KV cache optimization, and the acceleration of reasoning processes. Applications include AI search, web search, efficient LLM systems, retrieval augmented generation (RAG), AI for science, recommender systems, and mobile communication networks.
Prospective Interns:
I am looking for highly self-motivated research or applied interns (PhD or Master students) to join our Baidu Search Science team in Beijing! If you are interested in working with me in the area of AI Search and large language models, please email liyuchen02 {at} baidu.com.

Academic Awards

Best Student Paper Award, IEEE International Conference on Data Mining (ICDM), 2023
Best Paper Award, Journal Track, IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2023
Best Paper Award Nomination, Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2018

Publications (#equal contribution, †corresponding author)

[Textbook]

  1. 孔令和，刘雨桐，李豫晨，"人工智能技术与实践"，人民邮电出版社，2025，ISBN 978-7-115-67611-5.

[Technical Report]

  1. [Preprint] Yuchen Li, Hengyi Cai, Rui Kong, Xinran Chen, Jiamin Chen, Jun Yang, Haojie Zhang, Jiayi Li, Jiayi Wu, Yiqun Chen, Changle Qu, Keyi Kong, Wenwen Ye, Lixin Su, Xinyu Ma, Long Xia, Daiting Shi, Lingyong Yan, Jiashu Zhao, Junfeng Wang, Haoyi Xiong, Shuaiqiang Wang, Dawei Yin.
    Towards AI Search Paradigm. [pdf]
    Arxiv, 2025.

[Conference]

  1. [WWW'26] Yuchen Li, Rui Kong, Xinran Chen, Chengzhe Zhang, Jiamin Chen, Cheng Deng, Xinyu Ma, Haojie Zhang, Tianhao Peng, Hengyi Cai, Shuaiqiang Wang, Jiashu Zhao, Yongqi Zhang, Haoyi Xiong, Jimmy Huang, Lei Chen, Jun Wang, Dawei Yin.
    Probe-and-Fetch: Dynamic KV Cache Pruning for Accelerated Long-Context Inference in Web-Scale AI Search.
    The 35th Proceedings of the ACM on Web Conference, 2026.
  2. [KDD'26] Yuchen Li, Jiamin Chen, Xinran Chen, Zhiyu Li, Zhang Haojie, Rui Kong, Jiayi Li, Xinyu Ma, Hengyi Cai, Lixin Su, Shuaiqiang Wang, Jiashu Zhao, Yongqi Zhang, Haoyi Xiong, Linghe Kong, Lei Chen, Dawei Yin.
    Retain to Refine: Agent-Based Adaptive Question Answering via Query Routing and Long-Short Memory.
    The 32nd SIGKDD Conference on Knowledge Discovery and Data Mining, 2026.
  3. [AAAI'26] Qiyang Li, Rui Kong, Yuchen Li†, Hengyi Cai, Shuaiqiang Wang, Linghe Kong, Guihai Chen, Dawei Yin.
    AdaFuse: Accelerating Dynamic Adapter Inference via Token-Level Pre-Gating and Fused Kernel Optimization.
    The 40th Annual AAAI Conference on Artificial Intelligence, 2026.
  4. [AAAI'26] Shuo Feng, Zihan Wang, Yuchen Li, Rui Kong, Hengyi Cai, Shuaiqiang Wang, Gim Hee Lee, Piji Li, Shuqiang Jiang.
    VPN: Visual Prompt Navigation.
    The 40th Annual AAAI Conference on Artificial Intelligence, 2026.
  5. [AAAI'26] Ziheng Li, Hengyi Cai, Xiaochi Wei, Yuchen Li, Shuaiqiang Wang, Zhihong Deng, Dawei Yin.
    Efficient Thought Space Exploration through Strategic Intervention.
    The 40th Annual AAAI Conference on Artificial Intelligence, 2026.
  6. [ICLR'26] Siting Wang, Minnan Pei, Luoyang Sun, Cheng Deng, Yuchen Li, Kun Shao, Zheng Tian, Haifeng Zhang, Jun Wang.
    SpatialViz-Bench: A Cognitively-Grounded Benchmark for Diagnosing Spatial Visualization in MLLMs.
    The 14th International Conference on Learning Representations, 2026.
  7. [ICASSP'26] Zhenrong Cheng, Hengyi Cai, Hao Sun, Yuchen Li, Yan Zhang.
    A Data-Centric Framework for Scientific Natural Language Inference via LLM-Driven Information-Theoretic Augmentation.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2026.
  8. [ICASSP'26] Xuechen Liang, Yangfan He, Meiling Tao, Jianhui Wang, Yinghui Xia, Yuchen Li, Miao Zhang, Tianyu Shi, Jianyuan Ni.
    Memory-Evolution and Reflection-Augumented Agents.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2026.
  9. [ICASSP'26] Kun Li, Yangfan He, Shipeng Luo, Jianhui Wang, Yi Xin, Yijin Wang, Xinhang Yuan, Jiacheng Shi, Yuchen Li, Hongyang He, Jianyuan Ni.
    Dynamic Multi-Reward Optimization for Multi-Round Perference-Aligned Diffusion.
    IEEE International Conference on Acoustics, Speech, and Signal Processing, 2026.
  10. [KDD'25] Xinran Chen#, Yuchen Li#, Hengyi Cai, Zhuoran Ma, Xuanang Chen, Haoyi Xiong, Shuaiqiang Wang, Ben He, Le Sun, Dawei Yin.
    Multi-Agent Proactive Information Seeking with Adaptive LLM Orchestration for Non-Factoid Question Answering. [pdf]
    The 31st SIGKDD Conference on Knowledge Discovery and Data Mining, 2025.
  11. [KDD'25] Yuchen Li, Hao Zhang, Yongqi Zhang, Hengyi Cai, Mingxin Cai, Shuaiqiang Wang, Haoyi Xiong, Linghe Kong, Dawei Yin, Lei Chen.
    RankExpert: A Mixture of Textual-and-Behavioral Experts for Multi-Objective Learning-to-Rank in Web Search. [pdf]
    The 31st SIGKDD Conference on Knowledge Discovery and Data Mining, 2025.
  12. [KDD'25] Yuchen Li, Hao Zhang, Haojie Zhang, Hengyi Cai, Xinyu Ma, Shuaiqiang Wang, Haoyi Xiong, Zhaochun Ren, Maarten de Rijke, Dawei Yin.
    FULTR: A Large-Scale Fusion Learning to Rank Dataset and Its Application for Satisfaction-Oriented Ranking. [pdf]
    The 31st SIGKDD Conference on Knowledge Discovery and Data Mining, 2025.
  13. [KDD'25] Yuchen Li, Haoyi Xiong, Yongqi Zhang, Jiang Bian, Tianhao Peng, Xuhong Li, Shuaiqiang Wang, Linghe Kong, Dawei Yin.
    RankElectra: Semi-supervised Pre-training of Learning-to-Rank Electra for Web-scale Search. [pdf]
    The 31st SIGKDD Conference on Knowledge Discovery and Data Mining, 2025.
  14. [ICDE'25] Yuchen Li, Hao Zhang, Yongqi Zhang, Xinyu Ma, Wenwen Ye, Naifei Song, Shuaiqiang Wang, Haoyi Xiong, Dawei Yin, Lei Chen.
    M2oERank: Multi-objective Mixture-of-Experts Enhanced Ranking for Satisfaction-oriented Web Search. [pdf]
    The 41st IEEE International Conference on Data Engineering, 2025.
  15. [MM'25] Hui Wu, Haoquan Zhai, Yuchen Li, Hengyi Cai, Peirong Zhang, Yidan Zhang, Lei Wang, Chunle Wang, Yingyan Hou, Shuaiqiang Wang, Dawei Yin.
    MARA: A Multimodal Adaptive Retrieval-Augmented Framework for Document Question Answering.
    The 33rd ACM International Conference on Multimedia, 2025.
  16. [ACL'25] Hao Sun, Hengyi Cai, Yuchen Li, Xuanbo Fan, Xiaochi Wei, Shuaiqiang Wang, Yan Zhang, Dawei Yin.
    Enhancing Retrieval-Augmented Generation via Evidence Tree Search. [pdf]
    The 63rd Annual Meeting of the Association for Computational Linguistics, 2025.
  17. [AAAI'25] Tianhao Peng, Xuhong Li, Haitao Yuan, Yuchen Li, Haoyi Xiong.
    SOLA-GCL: Subgraph-oriented Learnable Augmentation Method for Graph Contrastive Learning. [pdf]
    The 39th Annual AAAI Conference on Artificial Intelligence, 2025.
  18. [ECAI'25] Mingxin Cai, Zexu Huang, Yuchen Li, Linghe Kong and Guihai Chen.
    VariGen: Controllable Image Generation Via Personalized Diffusion Framework.
    The 28th European Conference on Artificial Intelligence, 2025.
  19. [IJCAI'24] Yuchen Li, Haoyi Xiong, Linghe Kong, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, Dawei Yin.
    A Modular and Pre-trained Graphformer for Learning to Rank at Web-scale (Extended Abstract). [pdf]
    The 33rd International Joint Conference on Artificial Intelligence, 2024.
  20. [IJCAI'24] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
    A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search (Extended Abstract). [pdf]
    The 33rd International Joint Conference on Artificial Intelligence, 2024.
  21. [NeurIPS'24] Haizhou Du, Yijian Chen, Ryan Yang, Yuchen Li, Linghe Kong.
    HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links. [pdf]
    The 38th Conference on Neural Information Processing Systems, 2024.
  22. [KDD'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Qingzhong Wang, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
    S2phere: Semi-Supervised Pre-training for Web Search over Heterogeneous Learning to Rank Data. [pdf]
    The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
  23. [ICDM'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Zeyi Sun, Hongyang Chen, Shuaiqiang Wang, Dawei Yin.
    MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale. [pdf]
    The 23rd IEEE International Conference on Data Mining, 2023. (Acceptance Rate 9.37%) (Best Student Paper Award)
  24. [ECML PKDD'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, Dawei Yin.
    LtrGCN: Large-Scale Graph Convolutional Networks-based Learning to Rank for Web Search. [pdf]
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023.
  25. [DSAA'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
    GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search. [pdf]
    The 10th IEEE International Conference on Data Science and Advanced Analytics, 2023.
  26. [ECML PKDD'22] Yuchen Li, Haoyi Xiong, Linghe Kong, Rui Zhang, Dejing Dou, Guihai Chen.
    Meta Hierarchical Reinforced Learning to Rank for Recommendation: A Comprehensive Study in MOOCs. [pdf]
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022.
  27. [MOBICOM'21@Workshop] Junqin Huang, Linghe Kong, Jiejian Wu, Yutong Liu, Yuchen Li, Zhe Wang.
    Learning-based Congestion Control Simulator for Mobile Internet Education. [pdf]
    MobiArch Workshop, 2021. (held with ACM MOBICOM)
  28. [PRICAI'18] Chao Yu, Dongxu Wang, Tianpei Yang, Wenxuan Zhu, Yuchen Li, Hongwei Ge, Jiankang Ren.
    Adaptively Shaping Reinforcement Learning Agents via Human Reward. [pdf]
    The 15th Pacific Rim International Conference on Artificial Intelligence, 2018. (Best Paper Nomination)
[Journal]
  1. [TKDE] Yuchen Li, Zhonghao Lyu, Yongqi Zhang, Hao Zhang, Tianhao Peng, Haoyi Xiong, Shuaiqiang Wang, Linghe Kong, Guihai Chen, Dawei Yin.
    S3PRank: Towards Satisfaction-oriented Learning to Rank with Semi-supervised Pre-training.
    IEEE Transactions on Knowledge and Data Engineering, 2025.
  2. [TMC] Mingxin Cai, Chen Ma, Yuchen Li†, Zhonghao Lyu, Yutong Liu, Linghe Kong†, Guihai Chen.
    UCMM: Unsupervised Convolutional Networks for Accurate and Efficient Map Matching with Mobile Cellular Data. [pdf]
    IEEE Transactions on Mobile Computing, 2025.
  3. [npj AI] Tianhao Peng, Yuchen Li, Xuhong Li, Jiang Bian, Ning Sui, Shahid Mumtaz, Yanwu Xu, Linghe Kong, Haoyi Xiong.
    Pre-trained Molecular Language Models with Random Functional Group Masking. [pdf]
    npj Artificial Intelligence (Nature Portfolio), 2025.
  4. [TKDE] Tianhao Peng, Haitao Yuan, Yongqi Zhang, Yuchen Li, Peihong Dai, Qunbo Wang, Senzhang Wang, Wenjun Wu.
    TagRec: Temporal-Aware Graph Contrastive Learning with Theoretical Augmentation for Sequential Recommendation. [pdf]
    IEEE Transactions on Knowledge and Data Engineering, 2025.
  5. [TSC] Yuan Liao, Jiang Bian, Shilei Ji, Yuhui Yun, Shuo Wang, Yubo Zhang, Jiaming Chu, Tao Wang, Yuchen Li, Xuhong Li, Haoyi Xiong.
    SageCopilot: A LLM-empowered Autonomous Agent for Data Science as a Service.
    IEEE Transactions on Services Computing, 2025.
  6. [MLJ] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
    GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search. [pdf]
    Machine Learning, 2024. (IEEE DSAA Best Paper Award - Journal Track)
  7. [TSC] Haoyi Xiong, Bian Jiang, Yuchen Li†, Xuhong Li, Mengnan Du, Shuaiqiang Wang, Dawei Yin, Sumi Helal.
    When Search Engine Services meet Large Language Models: Visions and Challenges. [pdf]
    IEEE Transactions on Services Computing, 2024.
  8. [NMI] Ning Wang, Jiang Bian, Yuchen Li, Xuhong Li, Shahid Mumtaz, Linghe Kong, Haoyi Xiong.
    Multi-purpose RNA Language Modeling with Motif-aware Pre-training and Type-guided Fine-tuning. [pdf]
    Nature Machine Intelligence, 2024.
  9. [TWC] Zhonghao Lyu, Yuchen Li, Guangxu Zhu, Jie Xu, H. Vincent Poor, Shuguang Cui.
    Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm. [pdf]
    IEEE Transactions on Wireless Communications, 2024.
  10. [TKDE] Yuchen Li, Haoyi Xiong, Qingzhong Wang, Linghe Kong, Hao Liu, Haifang Li, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dejing Dou, Dawei Yin.
    COLTR: Semi-supervised Learning to Rank with Co-training and Over-parameterization for Web Search. [pdf]
    IEEE Transactions on Knowledge and Data Engineering, 2023.
  11. [TSC] Yuchen Li, Haoyi Xiong, Linghe Kong, Rui Zhang, Fangqin Xu, Guihai Chen, Minglu Li.
    MHRR: MOOCs Recommender Service with Meta Hierarchical Reinforced Ranking. [pdf]
    IEEE Transactions on Services Computing, 2023.
  12. [TKDD] Haoyi Xiong, Xiaofei Zhang, Jiamin Chen, Xinhao Sun, Yuchen Li, Zeyi Sun, Mengnan Du.
    Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective. [pdf]
    ACM Transactions on Knowledge Discovery from Data. [Major Revison]

Services

Professional Activities:
PC Member or Reviewer: KDD'26'25'24/WWW'26'25/SIGIR'25/NeurIPS'25/AAAI'26'25'24/IJCAI'26'25‘24/ICLR'26/WSDM'26'25/ECML PKDD'25'24/ICDM'25'23/ECAI'26/SIGIR-AP'25/CIKM'23/TMC/TKDD
Teaching Assistant:
CS339 Computer Networking [2020Fall, 2019Fall]
CS1603 Programming Design (C++) [2020Spring]