Qi Liu

Assistant Professor at the University of Hong Kong

The University of Hong Kong

Biography

I am an assistant professor at the Department of Computer Science, the University of Hong Kong, and a cofounder of Reka. I earned my Ph.D. in computer science from the University of Oxford. In the past, I obtained a Master of Science degree from the National University of Singapore, and a Bachelor of Engineering degree from Shandong University. My research interests include natural language processing and machine learning. My research is centered on enabling computers to comprehend human language. I also spent some time at Google DeepMind, Facebook AI Research, and Microsoft Research before and during my PhD study.

I have multiple fully-funded PhD, MPhil, postdoc, RA, and intern positions available at the University of Hong Kong. Email me for more information.

Reka is hiring for platform and machine learning. Email us for more information. We are an AGI company committed to the development of large foundation models.

Interests

Natural Language Processing
Machine Learning
Artificial Intelligence

Education

Ph.D. in Artificial Intelligence
University of Oxford, Advisors: Phil Blunsom, Matt Kusner
M.Sc in Computer Science
National University of Singapore, Advisor: Anthony K.H. Tung
BEng in Computer Science
Shandong University

Experiences

Research Scientist Intern

Google DeepMind

Jul 2020 – Jun 2021 London

Advisors: Phil Blunsom, Dani Yogatama, Lei Yu, Laura Rimell

Researcher

Facebook AI Research

Aug 2018 – Aug 2019 New York City

Advisors: Douwe Kiela, Maximilian Nickel

Research Intern

Microsoft Research

Mar 2018 – Jun 2018 Cambridge

Advisors: Alexander Gaunt, Marc Brockschmidt, Miltos Allamanis

Research Assistant

SUTD

Feb 2017 – Feb 2018 Singapore

Advisor: Yue Zhang

Research Intern

Microsoft Research

Sep 2016 – Dec 2016 Beijing

Advisors: Ying Yan, Thomas Moscibroda

Selected Awards

Forbes 30 Under 30 Asia List

Forbes Feb 2023

AMiner AI Most Influential Scholar

AMiner Jan 2022

Google DeepMind Scholarship

Google DeepMind Sep 2019

Lee Kuan Yew Global Business Plan Competition Winner (3 out of 550)

SMU Aug 2017

NUS Research Scholarship

NUS Sep 2014

Publications

Quickly discover relevant content by filtering publications.

Lei Li, Zhihui Xie, Mukai Li, Shunian Chen, Peiyi Wang, Liang Chen, Yazheng Yang, Benyou Wang, Lingpeng Kong, Qi Liu (2024). VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment. In EMNLP.

PDF

Chang Ma, Haiteng Zhao, Lin Zheng, Jiayi Xin, Qintong Li, Lijun Wu, Zhihong Deng, Yang Lu, Qi Liu, Lingpeng Kong (2024). Retrieved Sequence Augmentation for Protein Representation Learning. In EMNLP.

PDF

Zhihui Xie, Jiahui Gao, Lei Li, Zhenguo Li, Qi Liu, Lingpeng Kong (2024). Jailbreaking as a Reward Misspecification Problem. In arXiv.

PDF

Lei Li, Yuqi Wang, Runxin Xu, Peiyi Wang, Xiachong Feng, Lingpeng Kong, Qi Liu (2024). Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models. In ACL.

PDF

Mukai Li, Lei Li, Yuwei Yin, Masood Ahmed, Zhenguang Liu, Qi Liu (2024). Red Teaming Visual Language Models. In ACL Findings.

PDF

Peiyi Wang, Lei Li, Liang Chen, Dawei Zhu, Binghuai Lin, Yunbo Cao, Qi Liu, Tianyu Liu, Zhifang Sui (2024). Large Language Models are not Fair Evaluators. In ACL.

PDF

Reka team (2024). Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models. In Tech Report.

PDF

Reka team (2024). Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models. In Tech Report.

PDF

Yazheng Yang, Yuqi Wang, Sankalok Sen, Lei Li, Qi Liu (2024). Unleashing the Potential of Large Language Models for Predictive Tabular Tasks in Data Science. In arXiv.

PDF

Xijia Tao, Shuai Zhong, Lei Li, Qi Liu, Lingpeng Kong (2024). ImgTrojan: Jailbreaking Vision-Language Models with ONE Image. In arXiv.

PDF

Yazheng Yang, Yuqi Wang, Guang Liu, Ledell Wu, Qi Liu (2024). UniTabE: Pretraining a Unified Tabular Encoder for Heterogeneous Tabular Data. In ICLR.

PDF

Jiankai Sun (2023). A survey of reasoning with foundation models. In arXiv.

PDF

Lei Li, Jingjing Xu, Qingxiu Dong, Ce Zheng, Lingpeng Kong, Xu Sun, Qi Liu (2023). Can Language Models Understand Physical Concepts?. In EMNLP.

PDF

Haiteng Zhao, Shengchao Liu, Chang Ma, Hannan Xu, Jie Fu, Zhi-Hong Deng, Lingpeng Kong, Qi Liu (2023). GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning. In NeurIPS.

PDF

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu (2023). Evaluating Self-Supervised Learning for Molecular Graph Embeddings. In NeurIPS Datasets and Benchmarks.

PDF

Lei Li, Yuwei Yin, Shicheng Li, Liang Chen, Peiyi Wang, Shuhuai Ren, Mukai Li, Yazheng Yang, Jingjing Xu, Xu Sun, Lingpeng Kong, Qi Liu (2023). M3IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning. In arXiv.

PDF

Ante Wang, Linfeng Song, Qi Liu, Haitao Mi, Longyue Wang, Zhaopeng Tu, Jinsong Su, Dong Yu (2023). Search-engine-augmented dialogue response generation with cheaply supervised query production. In Artificial Intelligence.

PDF

Yazheng Yang, Zhou Zhao, Qi Liu (2023). MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style Transfer. In KDD.

PDF

Dingmin Wang, Shengchao Liu, Hanchen Wang, Linfeng Song, Jian Tang, Song Le, Bernardo Cuenca Grau, Qi Liu (2023). Augmenting Message Passing by Retrieving Similar Graphs. In ECAI.

PDF

Qi Liu, Zihuiwen Ye, Tao Yu, Phil Blunsom, Linfeng Song (2022). Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play. In EMNLP Findings.

PDF Code

Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva (2022). Causal Machine Learning: A Survey and Open Problems. In arXiv.

PDF

Qi Liu, Dani Yogatama, Phil Blunsom (2022). Relational Memory Augmented Language Models. In TACL.

PDF

Zhenguang Liu, Shuang Wu, Shuyuan Jin, Qi Liu, Shouling Ji, Shijian Lu, Li Cheng (2022). Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction. In PAMI.

PDF

Jean Kaddour, Yuchen Zhu, Qi Liu, Matthew J. Kusner, Ricardo Silva (2021). Causal Effect Inference for Structured Treatments. In NeurIPS.

PDF Code

Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matthew J. Kusner (2021). Unsupervised Point Cloud Pre-Training via View-Point Occlusion Completion. In ICCV.

PDF Code

Qi Liu, Lei Yu, Laura Rimell, Phil Blunsom (2021). Pretraining the Noisy Channel Model for Task-Oriented Dialogue. In TACL.

PDF

Qi Liu, Matt J. Kusner, Phil Blunsom (2021). Counterfactual Data Augmentation for Neural Machine Translation. In NAACL.

PDF

Dingmin Wang, Chenghua Lin, Qi Liu, Kam-Fai Wong (2021). Fast and Scalable Dialogue State Tracking with Explicit Modular Decomposition. In NAACL Short Paper.

PDF

Qi Liu, Matt J. Kusner, Phil Blunsom (2020). A Survey on Contextual Embeddings. In arXiv.

PDF

Yuan Zhuang, Zhenguang Liu, Peng Qian, Qi Liu, Xiang Wang, Qinming He (2020). Smart Contract Vulnerability Detection using Graph Neural Network. In IJCAI.

PDF

Shaolei Wang, Wanxiang Che, Qi Liu, Pengda Qin, Ting Liu, William Yang Wang (2020). Multi-Task Self-Supervised Learning for Disfluency Detection. In AAAI.

PDF

Qi Liu, Maximilian Nickel, Douwe Kiela (2019). Hyperbolic Graph Neural Networks. In NeurIPS.

PDF Code

Shuai Zhang, Yi Tay, Lina Yao, Qi Liu (2019). Quaternion Knowledge Graph Embedding. In NeurIPS.

PDF Code

Jiatao Gu, Qi Liu, Kyunghyun Cho (2019). Insertion-based Decoding with Automatically Inferred Generation Order. In TACL.

PDF

Zhenguang Liu, Shuang Wu, Shuyuan Jin, Qi Liu, Shijian Lu, Roger Zimmermann, Li Cheng (2019). Towards Natural and Accurate Future Motion Prediction of Humans and Animals. In CVPR.

PDF Code

Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt (2018). Constrained Graph Variational Autoencoders for Molecule Design. In NeurIPS.

PDF Code

Yue Zhang, Qi Liu, Linfeng Song (2018). Sentence-State LSTM for Text Representation. In ACL.

PDF Code

Qi Liu, Yue Zhang (2018). Mining Evidences for Concept Stock Recommendation. In NAACL.

PDF Code

Qi Liu, Yue Zhang, Jiangming Liu (2018). Learning Domain-specific Representations for Multi-Domain Sentiment Classification. In NAACL.

PDF Code

Qi Liu, Yue Zhang, Zhenguang Liu, Ye Yuan, Li Cheng, Roger Zimmermann (2018). Multi-modal Multi-task Learning for Automatic Dietary Assessment. In AAAI.

PDF

Yixuan Tang, Weilong Huang, Qi Liu, Anthony K.H. Tung, Xiaoli Wang, Jisong Yang, Beibei Zhang (2017). QALink: Enrich Text Documents with Relevant Q&A Site Contents. In CIKM.

PDF

Yang Li, Kai Zheng, Ying Yan, Qi Liu, Xiaofang Zhou (2017). EtherQL: A Query Layer for Blockchain. In DASFAA.

PDF Code

Zhenguang Liu, Yingjie Xia, Qi Liu, Qinming He, Yanxiang Chen, Roger Zimmermann (2017). Towards Personalized Activity Level Prediction in Community Question Answering Websites. In TOMM.

PDF

Butian Huang, Zhenguang Liu, Jianhai Chen, Anan Liu, Qi Liu, Qinming He (2017). Behavior Pattern Clustering in Blockchain Networks. In MTAP.

PDF

Zhenguang Liu, Luming Zhang, Qi Liu, Yifang Yin, Li Cheng, Roger Zimmermann (2016). Fusion of Magnetic and Visual Sensors for Indoor Localization: Infrastructure-free and More Effective. In TMM.

PDF

Shubham Goyal, Qi Liu, Khairina Tajul-Arifin, Waqas Awan, Bimlesh Wadhwa, Zhenguang Liu (2016). I Ate This: A Photo-based Food Journaling System with Expert Feedback. In SIGCHI Workshop.

PDF

Qiang Hu, Qi Liu, Xiaoli Wang, Anthony K.H. Tung, Shubham Goyal, Jisong Yang (2015). DocRicher: An Automatic Annotation System for Text Documents Using Social Media. In SIGMOD Demo Track.

PDF