Research

My research interests lie broadly in Natural Language Processing and Machine Learning. I am particularly intrigued by the interplay between knowledge and language. In recent years, I have been working on knowledge-intensive NLP problems such as Open-Domain Question Answering, Neural Retrieval, and more recently Retrieval-Augmented Language Models.

Previously, my PhD research was about learning deep representations for low-resource / zero-resource cross-lingual model transfer.

Publications

(* denotes equal contribution)

2024

RA-DIT: Retrieval-Augmented Dual Instruction Tuning
Xi Victoria Lin*, Xilun Chen*, Mingda Chen*, Weijia Shi, Maria Lomeli, Rich James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer and Scott Wen-tau Yih
ICLR 2024
proceedings, arXiv

Efficient Open Domain Multi-Hop Question Answering with Few-Shot Data Synthesis
Mingda Chen, Xilun Chen and Scott Wen-tau Yih
EACL 2024
proceedings, arXiv

2023

VideoOFA: Two-Stage Pre-Training for Video-to-Text Generation
Xilun Chen, Lili Yu, Wenhan Xiong, Barlas Oğuz, Yashar Mehdad, Scott Wen-tau Yih
arXiv 2305.03204
arXiv

How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval
Sheng-Chieh Lin*, Akari Asai, Minghan Li, Barlas Oguz, Jimmy Lin, Yashar Mehdad, Scott Wen-tau Yih, Xilun Chen*
Findings of EMNLP 2023
proceedings, arXiv, code, huggingface

CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval
Minghan Li*, Sheng-Chieh Lin, Barlas Oguz, Asish Ghoshal, Jimmy Lin, Yashar Mehdad, Scott Wen-tau Yih, Xilun Chen*
ACL 2023 (Oral)
proceedings, arXiv, code

Nonparametric Masked Language Modeling
Sewon Min, Weijia Shi, Mike Lewis, Xilun Chen, Scott Wen-tau Yih, Hannaneh Hajishirzi, Luke Zettlemoyer
Findings of ACL 2023
proceedings, arXiv, code

Task-aware Retrieval with Instructions
Akari Asai, Timo Schick, Patrick Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, Scott Wen-tau Yih
Findings of ACL 2023
proceedings, arXiv, code

A Study on the Efficiency and Generalization of Light Hybrid Retrievers
Man Luo, Shashank Jain, Anchit Gupta, Arash Einolghozati, Barlas Oguz, Debojeet Chatterjee, Xilun Chen, Chitta Baral, Peyman Heidari
ACL 2023 (short)
proceedings, arXiv

Hierarchical Video-Moment Retrieval and Step-Captioning
Abhay Zala*, Jaemin Cho*, Satwik Kottur, Xilun Chen, Barlas Oguz, Yashar Mehdad, Mohit Bansal
CVPR 2023
project page, proceedings, arXiv, code

2022

Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?
Xilun Chen, Kushal Lakhotia, Barlas Oguz, Anchit Gupta, Patrick Lewis, Stan Peshterliev, Yashar Mehdad, Sonal Gupta, Scott Wen-tau Yih
Findings of EMNLP 2022
proceedings, arXiv, code

Simple Local Attentions Remain Competitive for Long-Context Tasks
Wenhan Xiong, Barlas Oguz, Anchit Gupta, Xilun Chen, Diana Liskovich, Omer Levy, Scott Yih, Yashar Mehdad
NAACL-HLT 2022
proceedings, arXiv, code

CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training
Patrick Huber, Armen Aghajanyan, Barlas Oğuz, Dmytro Okhonko, Wen-tau Yih, Sonal Gupta, Xilun Chen
Findings of NAACL-HLT 2022
proceedings, arXiv, code

Domain-matched Pre-training Tasks for Dense Retrieval
Barlas Oguz*, Kushal Lakhotia*, Anchit Gupta*, Patrick Lewis, Vladimir Karpukhin, Aleksandra Piktus, Xilun Chen, Sebastian Riedel, Scott Yih, Sonal Gupta, Yashar Mehdad
Findings of NAACL-HLT 2022
proceedings, arXiv, code

UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering
Barlas Oguz*, Xilun Chen*, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Scott Yih
Findings of NAACL-HLT 2022
proceedings, arXiv, code

2021

Muppet: Massive Multi-task Representations with Pre-Finetuning
Armen Aghajanyan, Anchit Gupta, Akshat Shrivastava, Xilun Chen, Luke Zettlemoyer, Sonal Gupta
EMNLP 2021
proceedings, arXiv, huggingface

Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing
Asish Ghoshal, Xilun Chen, Sonal Gupta, Luke Zettlemoyer, Yashar Mehdad
ICLR 2021
proceedings

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
Proceedings of Machine Learning Research
competition page, proceedings, arXiv

2020

Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing
Xilun Chen, Asish Ghoshal, Yashar Mehdad, Luke Zettlemoyer, Sonal Gupta
EMNLP 2020
proceedings, arXiv, data

2019

Learning Deep Representations for Low-Resource Cross-Lingual Natural Language Processing
Xilun Chen
PhD Dissertation, Cornell University, May, 2019
pdf

Multi-Source Cross-Lingual Model Transfer: Learning What to Share
Xilun Chen, Ahmed Hassan Awadallah, Hany Hassan, Wei Wang and Claire Cardie
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019)
proceedings, bibtex, arXiv, code

2018

Unsupervised Multilingual Word Embeddings
Xilun Chen, Claire Cardie
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018)
proceedings, bibtex, arXiv, poster, code

Multinomial Adversarial Networks for Multi-Domain Text Classification
Xilun Chen, Claire Cardie
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018)
proceedings, bibtex, arXiv, poster, code

Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification
Xilun Chen, Yu Sun, Ben Athiwaratkun, Claire Cardie and Kilian Weinberger
Transactions of the Association for Computational Linguistics (TACL).
Article, bibtex (TACL), arXiv, bibtex (arXiv), talk@EMNLP2018, code

2017 and Before

A Rectangle Mining Method for Understanding the Semantics of Financial Tables
Xilun Chen, Laura Chiticariu, Marina Danilevsky, Alexandre Evfimievski and Prithviraj Sen
The 14th IAPR International Conference on Document Analysis and Recognition (ICDAR 2017)
proceedings, pdf, poster, bibtex, dataset

Combining Global Models for Parsing Universal Dependencies
Tianze Shi, Felix G. Wu, Xilun Chen and Yao Cheng
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies (CoNLL 2017)
pdf, bibtex

Price of Anarchy of Innovation Diffusion in Social Networks
Xilun Chen and Chenxia Wu, WINE 2014 (Poster)
pdf

Multi-Domain Adaptation for SMT Using Multi-Task Learning
Lei Cui, Xilun Chen, Dongdong Zhang, Shujie Liu,m Mu Li and Ming Zhou
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013)
pdf, bibtex

Education and Experiences

2013 - 2019, Ph.D. in Computer Sciense, Cornell University
2009 - 2013, B.S.E. in Computer Sciense, Shanghai Jiao Tong University

08.2019 - present, Research Scientist at Meta AI
05.2018 - 08.2018, Research Intern at Microsoft Research
05.2017 - 08.2017, PhD Intern at Facebook
05.2016 - 08.2016, Research Intern at IBM Research
05.2015 - 08.2015, PhD Intern at Google
05.2012 - 02.2013, Undergrad Research Intern at Microsoft Research Asia