August 18, 2020
Abstract. Deep metric learning papers from the past four years have consistently claimed great advances in accuracy, often more than doubling the performance of decade-old methods. In this paper, we take a closer look at the field to see if this is actually true. We find flaws in the experimental methodology of numerous metric learning papers, and show that the actual improvements over time have been marginal at best. Code is available at github.com/KevinMusgrave/powerful-benchmarker.
May 12, 2026
Corentin Bel, Linnea Evanson, Julien Gadonneix, Andrea Santos Revilla, Mingfang (Lucy) Zhang, Julie Bonnaire, Charlotte Caucheteux, Alexandre Défossez, Théo Desbordes, Pablo Diego-Simón, Shubh Khanna, Juliette Millet, Pierre Orhan, Saarang Panchavati, Antoine Ratouchniak, Alexis Thual, Hubert Jacob Banville, Jarod Levy, Jean Remi King, Josephine Raugel, Jérémy Rapin, Katelyn Begany, Marlene Careil, Simon Dahan, Sophia Houhamdi, Stéphane d'Ascoli, Teon Brooks, Yohann Benchetrit
May 12, 2026
May 06, 2026
Saarang Panchavati, Antoine Ratouchniak, Mingfang (Lucy) Zhang, Elisa Cascardi, Hubert Banville, Jarod Levy, Jean-Rémi King, Jérémy Rapin, Katelyn Begany, Marlene Careil, Simon Dahan, Stéphane d'Ascoli, Teon Brooks, Yohann Benchetrit
May 06, 2026
April 16, 2026
Nicola Cancedda, Pontus Stenetorp, Alexis Audran-Reiss, Alisia Lupidi, Anton Protopopov, Bassel Al Omari, Carole-Jean Wu, Derek Dunfield, Despoina Magka, Edan Toledo, Hela Momand, Ishita Mediratta, Jakob Foerster, Jean-Christophe Gagnon-Audet, Karen Hambardzumyan, Kelvin Niu, Martin Josifoski, Michael Kuchnik, Michael Shvartsman, Nicolas Baldwin, Parth Pathak, Rishi Hazra, Tatiana Shavrina, Thomas Simon Foster, Yoram Bachrach
April 16, 2026
April 14, 2026
Zijian Zhou, Bohao Tang, Pengfei Liu, Fei Zhang, Frost Xu, Hang Li (BizAI), Semih Gunel, Sen He, Soubhik Sanyal, Tao Xiang, Viktar Atliha, Zhe Wang
April 14, 2026

Our approach
Latest news
Foundational models