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Short Bio
I am a research scientist at Facebook AI Research (FAIR). My research interests are about multi-modal pre-training (CLIP and unCLIP), self-supervised Learning and Internet-scale data curation.
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.
Academic research interests: Lifelong Representation Learning, Open-world Learning, Sentiment Analysis, Question Answering and Conversational AI.
News
I'm open to invited talks about insights in my research, feel free to reach out.
Our team is looking for research interns in multi-modal pretraining, welcome to apply.
[Feb. 2020] I defended my Ph.D thesis, open-sourced my Ph.D. thesis.
[Sep. 2019] Ph.D proposal in lifelong representation learning for NLP.
Publication
2024
Demystifying CLIP Data (MetaCLIP)
Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer and Christoph Feichtenhofer.
[arxiv], [code]
2023
CiT: Curation in Training for Effective Vision-Language Data
ICCV 2023
Hu Xu, Saining Xie, Po-Yao Huang, Licheng Yu, Russell Howes, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer.
[paper], [code]
DINOv2: Learning Robust Visual Features without Supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski.
[paper], [code]
MAViL: Masked Audio-Video Learners
NeurIPS 2023
Po-Yao Huang, Vasu Sharma, Hu Xu, Chaitanya Ryali, Haoqi Fan, Yanghao Li, Shang-Wen Li, Gargi Ghosh, Jitendra Malik, Christoph Feichtenhofer.
[paper], [code]
Diffusion Models as Masked Autoencoders
ICCV 2023
Chen Wei, Karttikeya Mangalam, Po-Yao Huang, Yanghao Li, Haoqi Fan, Hu Xu, Huiyu Wang, Cihang Xie, Alan Yuille, Christoph Feichtenhofer.
[paper], [website]
2022
Adapting a Language Model While Preserving its General Knowledge
EMNLP 2022
Zixuan Ke, Yijia Shao, Haowei Lin, Hu Xu, Lei Shu and Bing Liu.
[paper], [code]
Continual Training of Language Models for Few-Shot Learning
EMNLP 2022
Zixuan Ke, Haowei Lin, Yijia Shao, Hu Xu, Lei Shu and Bing Liu.
[paper], [code]
Masked Autoencoders that Listen
NeurIPS 2022
Po-Yao Huang, Hu Xu, Juncheng Li, Alexei Baevski, Michael Auli, Wojciech Galuba, Florian Metze, Christoph Feichtenhofer.
[paper], [code]
CM3: A Causal Masked Multimodal Model of the Internet
Armen Aghajanyan, Bernie Huang, Candace Ross, Vladimir Karpukhin*, Hu Xu, Naman Goyal, Dmytro Okhonko, Mandar Joshi, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer.
[arxiv]
2021
VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding
EMNLP 2021
Hu Xu, Gargi Ghosh, Po-Yao Huang, Dmytro Okhonko, Armen Aghajanyan, Florian Metze, Luke Zettlemoyer, Christoph Feichtenhofer
[arxiv], [code]
HTLM: Hyper-text pre-training and prompting of language models
Armen Aghajanyan, Dmytro Okhonko, Mike Lewis, Mandar Joshi, Hu Xu, Gargi Ghosh, Luke Zettlemoyer
[arxiv]
VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding
ACL Findings 2021
Hu Xu, Gargi Ghosh, Po-Yao Huang, Prahal Arora, Masoumeh Aminzadeh, Christoph Feichtenhofer, Florian Metze, Luke Zettlemoyer
[arxiv], [code]
Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning
NeurIPS 2021
Zixuan Ke, Bing Liu, Nianzu Ma, Hu Xu and Lei Shu
[code]
CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks
EMNLP 2021
Zixuan Ke, Bing Liu, Hu Xu and Lei Shu
[code]
NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions
EMNLP Findings 2021
Zhiyu Chen, Honglei Liu, Hu Xu, Seungwhan Moon, Hao Zhou, Bing Liu
[arxiv], [code and data]
Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks
NAACL 2021
Zixuan Ke, Hu Xu and Bing Liu
[paper], [code]
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]
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