Welcome,

my name is 舒蕾. I am a Research Scientist at

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, specializing in large language models. Previously, I worked in Amazon AWS AI and Amazon Alexa AI for to-B and to-C conversational AI respectively. In 2020, I completed my Ph.D. in Computer Science at the University of Illinois at Chicago under Prof. Bing Liu's supervision. I worked with my advisor on sentiment analysis and lifelong learning. I also collaborated with Dr. Piero Molino and Dr. Gokhan Tur on Conversational AI, NLU/NLG research. I closely worked with Hu Xu (FAIR) on representation learning (language modeling, word embedding), open-world learning, meta-learning and question answering. Feel free to explore my work and reach out for discussions and collaborations. Let's move AI forward, together!


Selected Papers

(full list at Google Scholar)


2023

  • 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
    arXiv:2305.15685 [preprint]

2022

  • 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]
  • TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
    Yixuan Su, Fangyu Liu, Zaiqiao Meng, Tian Lan, Lei Shu, Ehsan Shareghi, Nigel Collier
    NAACL 2022 [preprint] [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]
  • Measuring and Reducing Model Update Regression in Structured Prediction for NLP
    Deng Cai, Elman Mansimov, Yi-An Lai, Yixuan Su, Lei Shu, Yi Zhang
    NeurIPS 2022 [preprint]
  • Continual Training of Language Models for Few-Shot Learning
    Zixuan Ke, Haowei Lin, Yijia Shao, Hu Xu, Lei Shu, Bing Liu
    EMNLP 2022 [preprint] [code]
  • Adapting a Language Model While Preserving its General Knowledge
    Zixuan Ke, Yijia Shao, Haowei Lin, Hu Xu, Lei Shu, Bing Liu
    EMNLP 2022 [preprint] [code]
  • Zero-Shot Aspect-Based Sentiment Analysis
    Lei Shu, Hu Xu, Bing Liu, Jiahua Chen
    arXiv:2202.01924 [preprint]

2021

  • ODIST: Open World Classification via Distributionally Shifted Instances
    Lei Shu, Yassine Benajiba, Saab Mansour, Yi Zhang
    EMNLP Findings 2021 [paper] [bib] [video]
  • CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks
    Zixuan Ke, Bing Liu, Hu Xu, Lei Shu
    EMNLP 2021 [code] [bib]
  • Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning
    Zixuan Ke, Bing Liu, Nainzu Ma, Hu Xu, Lei Shu
    NeurIPS 2021 [code]

2020

  • Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
    Hu Xu, Lei Shu, Philip S Yu, Bing Liu
    COLING 2020 [preprint]
  • Controllable Text Generation with Focused Variation
    Lei Shu, Alexandros Papangelis, Yi-Chia Wang, Gokhan Tur, Hu Xu, Zhaleh Feizollahi, Bing Liu, Piero Molino
    EMNLP Findings 2020 [preprint]
  • DomBERT: Domain-oriented Language Model for Aspect-based Sentiment Analysis
    Hu Xu, Bing Liu, Lei Shu, Philip S Yu
    EMNLP Findings 2020 [preprint]
  • Learning a Sequence of Sentiment Classification Tasks
    Zixuan Ke, Bing Liu, Hao Wang and Lei Shu
    ECML-PKDD 2020 [preprint][bib][code]

2019

  • Modeling Multi-Action Policy for Task-Oriented Dialogues
    Lei Shu, Hu Xu, Bing Liu, Piero Molino (Special thanks go to Alexandros Papangelis and Gokhan Tur)
    EMNLP 2019 [preprint][bib][code][poster]
  • Flexibly-Structured Model for Task-Oriented Dialogues
    Lei Shu, Piero Molino, Mahdi Namazifar, Hu Xu, Bing Liu, Huaixiu Zheng, Gokhan Tur
    SIGDIAL 2019 [preprint][bib][slides][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]
  • Open-world Learning and Application to Product Classification
    Hu Xu, Bing Liu, Lei Shu, P. Yu
    WWW 2019 [preprint][code]
  • Controlled CNN-based sequence labeling for aspect extraction
    Lei Shu, Hu Xu, Bing Liu
    arXiv 2019 [preprint]
  • A Failure of Aspect Sentiment Classifiers and an Adaptive Re-weighting Solution
    Hu Xu, Bing Liu, Lei Shu, Philip S Yu
    arXiv 2019 [preprint]

2018

  • Incorporating the Structure of the Belief State in End-to-End Task-Oriented Dialogue Systems
    Lei Shu, Piero Molino, Mahdi Namazifar, Bing Liu, Hu Xu, Huaixiu Zheng, Gokhan Tur
    NeurIPS 2018 Conversational AI Workshop [paper][bib]
  • Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction
    (Yelp Dataset Challenge Round 12 Grand Prize award)
    Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
    ACL 2018 [paper][bib][in-domain embedding][code][poster]
  • Lifelong Domain Word Embedding via Meta-Learning
    Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
    IJCAI 2018 [paper][bib][slides][code]
  • Dual Attention Network for Product Compatibility and Function Satisfiability Analysis
    Hu Xu, Sihong Xie, Lei Shu, Philip S. Yu
    AAAI 2018 [paper][bib][slides][dataset]
  • Unseen Class Discovery in Open-world Classification
    Lei Shu, Hu Xu, Bing Liu
    arXiv 2018 [preprint][bib]

2017 and before

  • DOC: Deep Open Classification of Text Documents
    Lei Shu, Hu Xu, Bing Liu
    EMNLP 2017 [paper][bib][video][dataset][code]
  • Lifelong Learning CRF for Supervised Aspect Extraction
    Lei Shu, Hu Xu, Bing Liu
    ACL 2017 [paper][bib][video]
  • Lifelong-RL: Lifelong Relaxation Labeling for Separating Entities and Aspects in Opinion Targets
    Lei Shu, Bing Liu, Hu Xu, Annice Kim
    EMNLP 2016 [paper][bib][video]

Professional Services

  • Aera/Session Chair for ACL 2023, ACL ARR 2022 2021, IJCAI 2018
  • PC member for ACL, EMNLP, NAACL, EACL, AACL, COLING, INLG, SLT, AAAI, NeurIPS, HLDS, WACV
  • Invited Reviewer of IEEE Transactions on Affective Computing, IEEE Access, IEEE/ACM Transactions on Audio, Speech, and Language Processing, Progress in Artificial Intelligence

Awards