Zobrazeno 1 - 10
of 9 341
pro vyhledávání: '"Bordes A"'
Autor:
Shen, Xiaoqian, Xiong, Yunyang, Zhao, Changsheng, Wu, Lemeng, Chen, Jun, Zhu, Chenchen, Liu, Zechun, Xiao, Fanyi, Varadarajan, Balakrishnan, Bordes, Florian, Liu, Zhuang, Xu, Hu, Kim, Hyunwoo J., Soran, Bilge, Krishnamoorthi, Raghuraman, Elhoseiny, Mohamed, Chandra, Vikas
Multimodal Large Language Models (MLLMs) have shown promising progress in understanding and analyzing video content. However, processing long videos remains a significant challenge constrained by LLM's context size. To address this limitation, we pro
Externí odkaz:
http://arxiv.org/abs/2410.17434
Autor:
Garau-Luis, Juan Jose, Bordes, Patrick, Gonzalez, Liam, Roller, Masa, de Almeida, Bernardo P., Hexemer, Lorenz, Blum, Christopher, Laurent, Stefan, Grzegorzewski, Jan, Lang, Maren, Pierrot, Thomas, Richard, Guillaume
Biological sequences encode fundamental instructions for the building blocks of life, in the form of DNA, RNA, and proteins. Modeling these sequences is key to understand disease mechanisms and is an active research area in computational biology. Rec
Externí odkaz:
http://arxiv.org/abs/2406.14150
Autor:
Bordes, Florian, Pang, Richard Yuanzhe, Ajay, Anurag, Li, Alexander C., Bardes, Adrien, Petryk, Suzanne, Mañas, Oscar, Lin, Zhiqiu, Mahmoud, Anas, Jayaraman, Bargav, Ibrahim, Mark, Hall, Melissa, Xiong, Yunyang, Lebensold, Jonathan, Ross, Candace, Jayakumar, Srihari, Guo, Chuan, Bouchacourt, Diane, Al-Tahan, Haider, Padthe, Karthik, Sharma, Vasu, Xu, Hu, Tan, Xiaoqing Ellen, Richards, Megan, Lavoie, Samuel, Astolfi, Pietro, Hemmat, Reyhane Askari, Chen, Jun, Tirumala, Kushal, Assouel, Rim, Moayeri, Mazda, Talattof, Arjang, Chaudhuri, Kamalika, Liu, Zechun, Chen, Xilun, Garrido, Quentin, Ullrich, Karen, Agrawal, Aishwarya, Saenko, Kate, Celikyilmaz, Asli, Chandra, Vikas
Following the recent popularity of Large Language Models (LLMs), several attempts have been made to extend them to the visual domain. From having a visual assistant that could guide us through unfamiliar environments to generative models that produce
Externí odkaz:
http://arxiv.org/abs/2405.17247
Autor:
Urbanek, Jack, Bordes, Florian, Astolfi, Pietro, Williamson, Mary, Sharma, Vasu, Romero-Soriano, Adriana
Curation methods for massive vision-language datasets trade off between dataset size and quality. However, even the highest quality of available curated captions are far too short to capture the rich visual detail in an image. To show the value of de
Externí odkaz:
http://arxiv.org/abs/2312.08578
Autor:
Bordes, Julien, Brown, James R., Watts, Daniel P., Bashkanov, Mikail, Newton, Ruth, Zachariou, Nicholas
Constraints on the quantum decoherence of entangled $\gamma$ quanta at the mega-electron-volt scale, such as those produced following positron annihilation, have remained elusive for many decades. We present the first statistically and kinematically
Externí odkaz:
http://arxiv.org/abs/2312.05045
The framed standard model (FSM), constructed to explain, with some success, why there should be 3 and apparently only 3 generations of quarks and leptons in nature falling into a hierarchical mass and mixing pattern, suggests also, among other things
Externí odkaz:
http://arxiv.org/abs/2311.06915
Autor:
Aurélien Mattuizzi, Fanny Sauvestre, Tiphaine Fargeix, Eoghann White, Claire Leibler, Marine Cargou, Nathalie Dugot-Senant, Isabelle Douchet, Dorothée Duluc, Cécile Bordes, Marie-Élise Truchetet, Christophe Richez, Édouard Forcade, Pierre Duffau, Jean-François Viallard, Loïc Sentilhes, Patrick Blanco, Estibaliz Lazaro
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Chronic histiocytic intervillositis of unknown origin (CHI) is a rare placental disorder associated with adverse pregnancy outcomes, frequent recurrence, and a lack of effective preventive strategies. Recent insights indicate a potential lin
Externí odkaz:
https://doaj.org/article/280de072b126442aae0d33eab281516f
Autor:
Hemmat, Reyhane Askari, Pezeshki, Mohammad, Bordes, Florian, Drozdzal, Michal, Romero-Soriano, Adriana
Current status quo in machine learning is to use static datasets of real images for training, which often come from long-tailed distributions. With the recent advances in generative models, researchers have started augmenting these static datasets wi
Externí odkaz:
http://arxiv.org/abs/2310.00158
Autor:
Bordes, Florian, Shekhar, Shashank, Ibrahim, Mark, Bouchacourt, Diane, Vincent, Pascal, Morcos, Ari S.
Synthetic image datasets offer unmatched advantages for designing and evaluating deep neural networks: they make it possible to (i) render as many data samples as needed, (ii) precisely control each scene and yield granular ground truth labels (and c
Externí odkaz:
http://arxiv.org/abs/2308.03977
Autor:
Bar, Amir, Bordes, Florian, Shocher, Assaf, Assran, Mahmoud, Vincent, Pascal, Ballas, Nicolas, Darrell, Trevor, Globerson, Amir, LeCun, Yann
Masked Image Modeling (MIM) is a promising self-supervised learning approach that enables learning from unlabeled images. Despite its recent success, learning good representations through MIM remains challenging because it requires predicting the rig
Externí odkaz:
http://arxiv.org/abs/2308.00566