Welcome! I’m a soon-to-graduate PhD student in Computer Science at University College London, co-advised by Prof. Sebastian Riedel and Prof. Pontus Stenetorp in the UCL NLP Group. Before joining UCL, I received my research-based master degree from the Hong Kong University of Science and Technology, advised by Prof. Qiang Yang.
Research Interest
My research interest lies at the intersection of Natural Language Processing (NLP) and Deep Learning. My current focus lies in Question Answering, Knowledge Base, and some related knowledge-intensive NLP tasks.
Publications (Google Scholar)
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks
Yuxiang Wu, Yu Zhao, Baotian Hu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel
EMNLP 2022 paper
Medical Dialogue Response Generation with Pivotal Information Recalling
Yu Zhao, Yunxin Li, Yuxiang Wu, Baotian Hu, Qingcai Chen, Xiaolong Wang, Yuxin Ding, Min Zhang
SIGKDD 2022 paper
Towards Fine-grained Causal Reasoning and QA
Linyi Yang, Zhen Wang, Yuxiang Wu, Jie Yang, Yue Zhang
Arxiv paper code
Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets
Yuxiang Wu, Matt Gardner, Pontus Stenetorp, Pradeep Dasigi
ACL 2022 paper code
DHA: Product Title Generation with Discriminative Hierarchical Attention for E-Commerce
Wenya Zhu, Yinghua Zhang, Yu Zhang, Yuhang Zhou, Yinfu Feng, Yuxiang Wu, Qing Da, Anxiang Zeng
PAKDD 2022 paper
Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints
Yuxiang Wu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel
ACL 2021 paper code
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them
Patrick Lewis, Yuxiang Wu, Linqing Liu, Pasquale Minervini, Heinrich Küttler, Aleksandra Piktus, Pontus Stenetorp, Sebastian Riedel
Transactions of the Association for Computational Linguistics (TACL) 2021 paper code
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
Sewon Min, Jordan Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih
NeurIPS 2020 paper website
Don’t Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering
Yuxiang Wu, Sebastian Riedel, Pasquale Minervini, Pontus Stenetorp
EMNLP 2020 paper slides
How Context Affects Language Models' Factual Predictions
Fabio Petroni, Patrick Lewis, Aleksandra Piktus, Tim Rocktäschel, Yuxiang Wu, Alexander H Miller, Sebastian Riedel
AKBC 2020 (Best Paper Award) paper code
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, Alexander H Miller, Sebastian Riedel
EMNLP 2019 paper code
Learning to Extract Coherent Summary via Deep Reinforcement Learning
Yuxiang Wu, Baotian Hu
AAAI 2018 paper
Integrating User and Agent Models: A Deep Task-Oriented Dialogue System
Weiyan Wang, Yuxiang Wu, Yu Zhang, Zhongqi Lu, Kaixiang Mo, Qiang Yang
Arxiv paper
End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification
Zheng Li, Yu Zhang, Ying Wei, Yuxiang Wu, Qiang Yang
IJCAI 2017 paper
Internships
Allen Institute for AI July-November, 2021
Facebook AI Research February-September, 2019
Tencent, WeChat Group March-November, 2017
Microsoft Research Asia December 2014-July, 2015
University of Hong Kong July-August, 2014
Competitions
| Year | Competition | Track | Rank/Prize |
|---|---|---|---|
| 2020 | Efficient QA | System Under 500Mb | 1st |
| 2020 | Efficient QA | Smallest Systems Achieving 25% Accuracy | 1st |
| 2015 | Large Scale Visual Recognition Challenge (ImageNet) | Video Object Detection | 5th |
| 2014 | SAT Competition 2014 | Sequential Random SAT Track | 9th |
| 2013 | The Mathematical Contest in Modeling | ICM Problem C | Meritorious Winner |
Teaching Assistant
| Year | Module | Institute |
|---|---|---|
| 2019 Spring | COMP0089 Advanced Reinforcement Learning and Deep Learning | UCL |
| 2019 Spring | COMP0087 Statistical Natural Language Processing | UCL |
| 2019 Fall | COMP0137 Machine Vision | UCL |
| 2017 Fall | MSBD600B Deep Learning | HKUST |
Academic Services
Program Committee: ACL 2020, EMNLP 2020, Repl4NLP Workshop 2020, SustaiNLP Workshop 2020, EACL 2021, NAACL 2021, ACL 2021, EMNLP 2021, Repl4NLP 2021, MRQA Workshop 2021, CCKS 2021, ACL 2022, EMNLP 2022, AKBC 2022, AAAI 2023, EACL 2023