no code implementations • JEPTALNRECITAL 2017 • Jos{\'e} Moreno, Romaric Besan{\c{c}}on, Romain Beaumont, Eva D{'}hondt, Anne-Laure Ligozat, Sophie Rosset, Xavier Tannier, Brigitte Grau
La d{\'e}sambigu{\"\i}sation d{'}entit{\'e}s (ou liaison d{'}entit{\'e}s), qui consiste {\`a} relier des mentions d{'}entit{\'e}s d{'}un texte {\`a} des entit{\'e}s d{'}une base de connaissance, est un probl{\`e}me qui se pose, entre autre, pour le peuplement automatique de bases de connaissances {\`a} partir de textes.
no code implementations • 2 Sep 2021 • Jules Samaran, Ugo Tanielian, Romain Beaumont, Flavian vasile
Current recommendation approaches help online merchants predict, for each visiting user, which subset of their existing products is the most relevant.
2 code implementations • 3 Nov 2021 • Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, Aran Komatsuzaki
Multi-modal language-vision models trained on hundreds of millions of image-text pairs (e. g.
3 code implementations • NeurIPS 2022 Datasets and Benchmarks 2022 • Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev
We show successful replication and fine-tuning of foundational models like CLIP, GLIDE and Stable Diffusion using the dataset, and discuss further experiments enabled with an openly available dataset of this scale.
3 code implementations • CVPR 2023 • Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev
To address these limitations, we investigate scaling laws for contrastive language-image pre-training (CLIP) with the public LAION dataset and the open-source OpenCLIP repository.
Ranked #1 on Zero-Shot Image Classification on Country211 (using extra training data)
1 code implementation • NeurIPS 2023 • Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt
Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model architectures or training algorithms.