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Welcome,

my name is 舒蕾. I am a Research Scientist at Google Deepmind, specializing in Agentic AI and large multimodal and language models. I am a core contributor to Project Astra and Gemini. Prior to this, I worked at Amazon AWS AI and Amazon Alexa AI. In 2020, I earned my Ph.D. in Computer Science at the University of Illinois at Chicago under Prof. Bing Liu's supervision. I also worked as a research intern at Uber AI Lab, where I was advised by Dr. Piero Molino and Dr. Gokhan Tur. I am the winner of Yelp dataset challenge.

News
  • Our new, Project Astra, launched at Google I/O 2025. I'm proud to lead modeling for Computer Control & Visual Overlay.
    Check out our demos:
    • Project Astra Action Intelligence
    • Project Astra x Education (Visual Tutor)
  • I am no longer seeking a student researcher, as the position has been filled. Thank you to everyone who expressed interest. I am seeking a student researcher for Summer/Winter 2025 to collaborate on cutting-edge Agentic AI projects. If you are interested, please apply via Google Careers and send me an email once the recruiter confirms your inclusion in the candidate pool.
Publications 2024

    • RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting
      Lei Shu, Liangchen Luo, Jayakumar Hoskere, Yun Zhu, Canoee Liu, Simon Tong, Jindong Chen, Lei Meng
      AAAI 2024 [paper]
    • Fusion-Eval: Integrating Assistant Evaluators with LLMs
      Lei Shu, Nevan Wichers, Liangchen Luo, Yun Zhu, Yinxiao Liu, Jindong Chen, Lei Meng
      EMNLP 2024 Industry [paper]
    • Enhancing Reinforcement Learning with Dense Rewards from Language Model Critic
      Meng Cao, Lei Shu, Lei Yu, Yun Zhu, Nevan Wichers, Yinxiao Liu, Lei Meng
      EMNLP 2024 Main [paper]
    • Improve Mathematical Reasoning in Language Models by Automated Process Supervision
      Liangchen Luo, Yinxiao Liu, Rosanne Liu, Samrat Phatale, Harsh Lara, Yunxuan Li, Lei Shu, Yun Zhu, Lei Meng, Jiao Sun, Abhinav Rastogi
      arXiv:2406.06592 [preprint]
    • Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection
      Yun Zhu, Jia-Chen Gu, Caitlin Sikora, Ho Ko, Yinxiao Liu, Chu-Cheng Lin, Lei Shu, Liangchen Luo, Lei Meng, Bang Liu, Jindong Chen
      arXiv:2405.16178 [preprint]
    2023 and before (Selected Papers)

  • Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
    Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai, Yi Zhang
    ACL 2022 [preprint] [bib] [code]
  • Zero-Shot Out-of-Distribution Detection Based on the Pretrained Model CLIP
    Sepideh Esmaeilpour, Bing Liu, Eric Robertson, Lei Shu
    AAAI 2022 [paper] [bib]
  • Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning
    Zixuan Ke, Bing Liu, Nainzu Ma, Hu Xu, Lei Shu
    NeurIPS 2021 [code]
  • BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis
    Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
    NAACL 2019 [preprint][code][dataset]
  • Unseen Class Discovery in Open-world Classification
    Lei Shu, Hu Xu, Bing Liu
    arXiv 2018 [preprint][bib]
  • DOC: Deep Open Classification of Text Documents
    Lei Shu, Hu Xu, Bing Liu
    EMNLP 2017 [paper][bib][video][dataset][code]
View More Publications
Services and Awards

I actively serve as an Area Chair for ACL ARR (covering ACL, EMNLP, NAACL, EACL, and COLING) and as a reviewer for conferences including NeurIPS, ICML, ICLR, AAAI, IJCAI, WACV, and others.

View More Services and Awards