About me

I am a Quant Research Lead at Point72, applying NLP to financial data.

Previously, I was an AI Resident at Google Research NYC, working on NLP and before that a research scientist at BenevolentAI. I hold a MS in Data Science from New York University, where I conducted research in the ML² group at CILVR, working with Sam Bowman. I have also worked on Computer Vision for Medical Imaging with Krzysztof Geras and Kyunghyun Cho.

Before that, I did a double degree in France between HEC Paris (Management) and ENSAE ParisTech (Statistics).

Publications

Natural Language Processing

• PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts Stephen H Bach, Victor Sanh, Zheng-Xin Yong, Albert Webson, Colin Raffel, Nihal V Nayak, Abheesht Sharma, Taewoon Kim, M Saiful Bari, Thibault Févry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged S Al-shaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Mike Tian-Jian Jiang, Alexander M Rush ACL 2022 2022 Paper - Code

• Multitask Prompted Training Enables Zero-Shot Task Generalization
  Victor Sanh, Albert Webson, Colin Raffel, Stephen H Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, Alexander M Rush
  ICLR 2022, Spotlight 2021
  Paper - Code & Demo

• Do Transformer Modifications Transfer Across Implementations and Applications?
  Sharan Narang, Hyung Won Chung, Yi Tay, William Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel
  EMNLP 2020
  2021
  Paper

• Rethinking embedding coupling in pre-trained language models
  ^* Hyung Won Chung, ^* Thibault Févry, Henry Tsai, Melvin Johnson, Sebastian Ruder
  2020
  ICLR 2021
  Paper

• Entities as experts: Sparse memory access with entity supervision
  Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, Eunsol Choi, Tom Kwiatkowski 2020
  EMNLP 2020
  Paper - Talk

• Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking
  ^* Thibault Févry, ^* Nicholas FitzGerald, Livio Baldini Soares, Tom Kwiatkowski
  AKBC 2020
  Paper - Talk

• Learning Cross-Context Entity Representations from Text
  Jeffrey Ling, Nicholas FitzGerald, Zifei Shan, Livio Baldini Soares, Thibault Févry, David Weiss, Tom Kwiatkowski 2019
  Paper

• Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks
  ^* Jason Phang, ^* Thibault Févry, Sam Bowman
  2018
  Paper - Code & Models

• Unsupervised Sentence Compression using Denoising Auto-Encoders
  ^* Thibault Févry, ^* Jason Phang
  CoNLL 2018
  Paper - Code - Poster - NYU Blog

Medical Imaging

• Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening
  Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Masha Zorin, Stanisław Jastrzebski, Thibault Févry, Joe Katsnelson, Eric Kim, Stacey Wolfson, Ujas Parikh, Sushma Gaddam, Leng Leng Young Lin, Kara Ho, Joshua D. Weinstein, Beatriu Reig, Yiming Gao, Hildegard Toth, Kristine Pysarenko, Alana Lewin, Jiyon Lee, Krystal Airola, Eralda Mema, Stephanie Chung, Esther Hwang, Naziya Samreen, S. Gene Kim, Laura Heacock, Linda Moy, Kyunghyun Cho, and Krzysztof J. Geras, Preprint, 2018
  IEEE Transactions of Medical Imaging, 2019
  Best Paper @ICML 2019 AI for Social Good
  Paper - Code & Models - Poster - Medium

• Improving localization-based approaches for breast cancer screening exam classification
  Thibault Févry, Jason Phang, Nan Wu, S. Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras
  MIDL 2019 Extended Abstract
  Paper - Poster