
Research Scientist Intern at
DeepMind
London, UK
2022.06 ~ 2022.10
Supervised by Arthur Mensch, Igor Babuschkin, and Laurent Sifre
likicode@gmail.com
Hi! I'm Linqing Liu, a PhD student in University College London's Natural Language Processing Group, co-supervised by Prof. Pontus Stenetorp and Prof. Sebastian Riedel. Before that, I received my thesis-based master degree at University of Waterloo, supervised by Prof. Jimmy Lin. I got my bachelor degree from School of Software Engineering at Tongji University, Shanghai.
My work focuses on the intersection of Deep Learning and Natural Language Processing, with the goal of building accurate and efficient systems (e.g. question answering) that enable individuals to access the most up-to-date knowledge in real-world scenarios. My research spans across building large-scale retrieval-augmented language models, developing more generalizable open domain QA systems, and interpreting model behavior.
I'm now on the job market. This is my CV. Please don't hesitate to drop me a message about any career opportunities!
What the DAAM: Interpreting Stable Diffusion Using Cross Attention
Raphael Tang*, Linqing Liu*, Akshat Pandey, Zhiying Jiang, Gefei Yang, Karun Kumar, Pontus Stenetorp, Jimmy Lin and Ferhan Ture
ACL, 2023
Query Expansion Using Contextual Clue Sampling with Language Models
Linqing Liu, Minghan Li, Jimmy Lin, Sebastian Riedel and Pontus Stenetorp
Arxiv Preprint, 2022
When Do Flat Minima Optimizers Work?
Jean Kaddour*, Linqing Liu*, Ricardo Silva and Matt J. Kusner (*: equal contribution)
NeurIPS, 2022
Challenges in Generalization in Open Domain Question Answering
Linqing Liu, Patrick Lewis, Sebastian Riedel and Pontus Stenetorp
NAACL Findings, 2022
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them
Patrick Lewis, Yuxiang Wu, Linqing Liu, Pasquale Minervini, Heinrich Kuttler, Aleksandra Piktus, Pontus Stenetorp, Sebastian Riedel
TACL, 2021
[Project]
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
Sewon Min et al.
NeurIPS Competition and Demonstration Track, 2021
Controllable Abstractive Dialogue Summarization with Sketch Supervision
Chien-Sheng Wu*, Linqing Liu*, Wenhao Liu, Pontus Stenetorp, Caiming Xiong (*: equal contribution)
ACL-IJCNLP Findings, 2021
[Project]
MKD: a Multi-Task Knowledge Distillation Approach for Pretrained Language Models
Linqing Liu, Huan Wang, Jimmy Lin, Richard Socher and Caiming Xiong
Arxiv Preprint, 2020
Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling
Linqing Liu, Wei Yang, Jinfeng Rao, Raphael Tang and Jimmy Lin
EMNLP, 2019
[Project]   [slides]
Bridging the Gap between Relevance Matching and Semantic Matching with Hierarchical Co-Attention Network
Jinfeng Rao, Linqing Liu, Yi Tay, Wei Yang, Peng Shi and Jimmy Lin
EMNLP, 2019
[Project]
Distilling Task-Specific Knowledge from BERT into Simple Neural Networks
Raphael Tang*, Yao Lu*, Linqing Liu*, Lili Mou, Olga Vechtomova, Jimmy Lin (*: equal contribution)
Arxiv Preprint, 2019
Generative Adversarial Network for Abstractive Text Summarization
Linqing Liu, Yao Lu, Min Yang, Qiang Qu, and Jia Zhu
The 30th AAAI Conference on Artificial Intelligence (AAAI, student poster), 2018
[supplementary file][output summary]
Detecting "Smart" Spammers On Social Network: A Topic Model Approch
Linqing Liu, Yao Lu, Ye Luo, Renxian Zhang, Laurent Itti, and Jianwei Lu
the North American Chapter of the Association for Computational Linguistics (NAACL, student session). 2016
[poster][dataset]
Research Scientist Intern at
DeepMind
London, UK
2022.06 ~ 2022.10
Supervised by Arthur Mensch, Igor Babuschkin, and Laurent Sifre
Research Intern at
Salesforce Research
Palo Alto, USA
2019.09 ~ 2020.08
Supervised by Caiming Xiong
Research Intern at
Software Analysis and Intelligence Lab (SAIL)
Queen's University, Kingston, Canada
2016.06 ~ 2016.09
Supervised by Ahmed E. Hassan and
Cor-Paul Bezemer