About me

I am a researcher at Point72, applying NLP to financial data. I am interested in building robust general-purpose representations of language for transfer learning.

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). I also did internships at Morgan Stanley, Eleven Strategy and Younited Credit.


Natural Language Processing

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

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

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

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

  • Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks
    * Jason Phang, * Thibault Févry, Sam Bowman
    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