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Short Bio

I am a research scientist at Facebook AI Research (FAIR). Previously, I received my Ph.D in computer science from University of Illinois at Chicago, advised by Prof. Philip S. Yu and Prof. Bing Liu. I got my master in microelectronics from Peking University.

During my Ph.D. study I also work as a research intern at Facebook AI, Amazon AI and WeChat AI lab. I am the winner of Yelp dataset challenge.

Google Scholar, GitHub, Linkedin, Twitter, Medium

Research Interest

I'm open to collaboration on research or guidance on interesting projects in NLP. Self-supervised Learning
Lifelong Representation Learning and Open-world Learning
Sentiment Analysis
Question Answering
Conversational AI

News

I defended my Ph.D thesis, open-sourced my Ph.D. thesis.
Ph.D proposal in lifelong representation learning for NLP.


Publication

2020

Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
COLING 2020
Hu Xu, Lei Shu, Philip S. Yu, Bing Liu
[arxiv], [code]

User Memory Reasoning for Conversational Recommendation
COLING 2020
Hu Xu, Seungwhan Moon, Honglei Liu, Bing Liu, Pararth Shah, Bing Liu, Philip S. Yu
[arxiv]

DomBERT: Domain-oriented Language Model for Aspect-based Sentiment Analysis
EMNLP Findings, 2020
Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
[arxiv]

Controllable Text Generation with Focused Variation
EMNLP Findings, 2020
Lei Shu, Alexandros Papangelis, Yi-Chia Wang, Gokhan Tur, Hu Xu, Zhaleh Feizollahi, Bing Liu, Piero Molino
[arxiv]

NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions
Zhiyu Chen, Honglei Liu, Hu Xu, Seungwhan Moon, Hao Zhou, Bing Liu
[arxiv]

2019

Open-world Learning and Application to Product Classification
The Web Conference (WWW 2019)
Hu Xu, Bing Liu, Lei Shu, P. Yu
[arxiv], [code]

BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis
(using BERT for review-based tasks)
2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019)
Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
[paper], [arxiv], [code], [dataset]

Flexibly-Structured Model for Task-Oriented Dialogues
SIGDIAL 2019
Lei Shu, Piero Molino, Mahdi Namazifar, Bing Liu, Hu Xu, Huaixiu Zheng and Gokhan Tur
[paper], [code]

Modeling Multi-Action Policy for Task-Oriented Dialogues
2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019)
Lei Shu, Hu Xu, Bing Liu and Piero Molino

Review Conversational Reading Comprehension
arXiv 1902.00821
Hu Xu, Bing Liu, Lei Shu and Philip S. Yu
[paper]

2018

Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction
the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018)
(This paper won Yelp Dataset Challenge Round 12 Grand Prize Award)
Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
[paper], [code], [domain embedding], [bib], [poster]

Lifelong Domain Word Embedding via Meta-Learning
International Joint Conference on Artificial Intelligence (IJCAI 2018)
Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
[arxiv], [code], [bib], [slides]

Dual Attention Network for Product Compatibility and Function Satisfiability Analysis
AAAI Conference on Artificial Intelligence (AAAI 2018)
(This paper focuses on complementary aspect extraction and polarity classification from question-answering pairs)
Hu Xu, Sihong Xie, Lei Shu, Philip S. Yu
[paper], [dataset], [bib], [slides]

Incorporating the Structure of the Belief State in End-to-End Task-Oriented Dialogue Systems
NeurIPS 2018 Conversational AI Workshop
Lei Shu, Piero Molino, Mahdi Namazifar, Bing Liu, Hu Xu, Huaixiu Zheng, Gokhan Tur
[paper]

Unseen Class Discovery in Open-world Classification
preprint arXiv:1801.05609
Lei Shu, Hu Xu, Bing Liu
[arxiv]

2017

Product Function Need Recognition via Semi-supervised Attention Network
IEEE International Conference on Big Data 2017 (IEEE Bigdata 2017)
Hu Xu, Sihong Xie, Lei Shu, Philip S. Yu
[paper], [dataset], [bib]

DOC: Deep Open Classification of Text Documents
2017 Conference on Empirical Methods in Natural Language Processing (EMNLP 2017)
Lei Shu, Hu Xu, Bing Liu
[paper], [bib], [code: EMNLP2017, www2019]

Lifelong Learning CRF for Supervised Aspect Extraction
the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017)
Lei Shu, Hu Xu, Bing Liu
[paper], [bib]

2016

Mining Compatible/Incompatible Entities from Question and Answering via Yes/No Answer Classification using Distant Label Expansion
arXiv preprint arXiv:1612.04499
Hu Xu, Lei Shu, Jingyuan Zhang, Philip S. Yu
[paper], [dataset], [bib]

CER: Complementary Entity Recognition via Knowledge Expansion on Large Unlabeled Product Reviews
(Previous title: Sentence-level Extraction of Complementary Entities using Large Unlabeled Product Reviews)
IEEE International Conference on Big Data 2016 (IEEE Bigdata 2016)
Hu Xu, Sihong Xie, Lei Shu, Philip S. Yu
[paper], [slides], [data], [bib]

Lifelong-RL: Lifelong Relaxation Labeling for Separating Entities and Aspects in Opinion Targets
(Previous title: Separating entities and aspects in opinion targets using lifelong graph labeling)
2016 Conference on Empirical Methods in Natural Language Processing (EMNLP 2016)
Lei Shu, Bing Liu, Hu Xu, and Annice Kim
[paper], [slides], [bib]

2013

Planning Paths with Fewer Turns on Grid Maps
AAAI Sixth Annual Symposium on Combinatorial Search
Hu Xu, Lei Shu, May Huang
[paper], [dataset], [bib]

High-speed and accurate laser scan matching using classified features
IEEE International Symposium on Robotic and Sensors Environments (ROSE), 2013
Lei Shu, Hu Xu, May Huang
[check IEEE database], [bib]

2011

Accuracy analysis of power characterization and modeling
Convergence and Hybrid Information Technology Springer Berlin Heidelberg
Xiaolan Bai, Hu Xu and May Huang
[check Springer Database]


Service

PC Members: ACL 2020, EMNLP 2020/2019, AACL 2020, AAAI 2020/2019, IJCAI 2018-2020, NAACL 2019, COLING 2020, WWW 2019
External Reviewer, ACL 2019, AAAI 2018, IEEE DSAA 2016
Journal Reviewer: TPAMI, JAIR, TKDD, Natural Language Engineering, IEEE Transactions on Affective Computing, Transactions on Asian and Low-Resource Language Information Processing


Award

Yelp Dataset Challenge Grand Prize Award
AAAI Scholarship
Presenter Award, University of Illinois at Chicago
Travel Award, IEEE International Conference on Big Data
May 4th Scholarship, Peking University


Talk

Google AI: Learning for Open-world, Host: Dr. Qi Li, 2019
Facebook Conversational AI Summit, Host: Dr. Alborz Geramifard 2019
Amazon Alexa AI: Learning for Open-world, Host: Dr. Young-bum Kim, 2019
AAAI 2018: Dual Attention Network for Product Compatibility and Function Satisfiability Analysis, 2018
Bigdata 2016: CER: Complementary Entity Recognition via Knowledge Expansion on Large Unlabeled Product Reviews, 2016
SoCS 2013: Planning Paths with Fewer Turns on Grid Maps, 2013