Zobrazeno 1 - 10
of 29 922
pro vyhledávání: '"A A, Kale"'
Visualizations play a critical role in validating and improving statistical models. However, the design space of model check visualizations is not well understood, making it difficult for authors to explore and specify effective graphical model check
Externí odkaz:
http://arxiv.org/abs/2408.16702
Labeling visual data is expensive and time-consuming. Crowdsourcing systems promise to enable highly parallelizable annotations through the participation of monetarily or otherwise motivated workers, but even this approach has its limits. The solutio
Externí odkaz:
http://arxiv.org/abs/2409.00048
Autor:
Khuntia, Abhilash, Kale, Shubham
The significance of emotion detection is increasing in education, entertainment, and various other domains. We are developing a system that can identify and transform facial expressions into emojis to provide immediate feedback.The project consists o
Externí odkaz:
http://arxiv.org/abs/2407.04560
Advancements in DeepFake (DF) audio models pose a significant threat to voice authentication systems, leading to unauthorized access and the spread of misinformation. We introduce a defense mechanism, SecureSpectra, addressing DF threats by embedding
Externí odkaz:
http://arxiv.org/abs/2407.00913
Autor:
Botteon, A., van Weeren, R. J., Eckert, D., Gastaldello, F., Markevitch, M., Giacintucci, S., Brunetti, G., Kale, R., Venturi, T.
Abell 754 is a rich galaxy cluster at $z=0.0543$ and is considered the prototype of a major cluster merger. Like many dynamically unrelaxed systems, it hosts diffuse radio emission on Mpc-scales. Extended synchrotron sources in the intra-cluster medi
Externí odkaz:
http://arxiv.org/abs/2406.18983
For many years, systems running Nvidia-based GPU architectures have dominated the heterogeneous supercomputer landscape. However, recently GPU chipsets manufactured by Intel and AMD have cut into this market and can now be found in some of the worlds
Externí odkaz:
http://arxiv.org/abs/2406.10362
Autor:
Hiwarkhedkar, Sharayu, Mittal, Saloni, Magdum, Vidula, Dhekane, Omkar, Joshi, Raviraj, Kale, Geetanjali, Ladkat, Arnav
For green AI, it is crucial to measure and reduce the carbon footprint emitted during the training of large language models. In NLP, performing pre-training on Transformer models requires significant computational resources. This pre-training involve
Externí odkaz:
http://arxiv.org/abs/2404.18228
Autor:
Lebrat, Martin, Kale, Anant, Kendrick, Lev Haldar, Xu, Muqing, Gang, Youqi, Nikolaenko, Alexander, Sachdev, Subir, Greiner, Markus
Strongly correlated materials feature multiple electronic orbitals which are crucial to accurately understand their many-body properties, from cuprate materials to twisted bilayer graphene. In such multi-band models, quantum interference can lead to
Externí odkaz:
http://arxiv.org/abs/2404.17555
Autor:
Botev, Aleksandar, De, Soham, Smith, Samuel L, Fernando, Anushan, Muraru, George-Cristian, Haroun, Ruba, Berrada, Leonard, Pascanu, Razvan, Sessa, Pier Giuseppe, Dadashi, Robert, Hussenot, Léonard, Ferret, Johan, Girgin, Sertan, Bachem, Olivier, Andreev, Alek, Kenealy, Kathleen, Mesnard, Thomas, Hardin, Cassidy, Bhupatiraju, Surya, Pathak, Shreya, Sifre, Laurent, Rivière, Morgane, Kale, Mihir Sanjay, Love, Juliette, Tafti, Pouya, Joulin, Armand, Fiedel, Noah, Senter, Evan, Chen, Yutian, Srinivasan, Srivatsan, Desjardins, Guillaume, Budden, David, Doucet, Arnaud, Vikram, Sharad, Paszke, Adam, Gale, Trevor, Borgeaud, Sebastian, Chen, Charlie, Brock, Andy, Paterson, Antonia, Brennan, Jenny, Risdal, Meg, Gundluru, Raj, Devanathan, Nesh, Mooney, Paul, Chauhan, Nilay, Culliton, Phil, Martins, Luiz Gustavo, Bandy, Elisa, Huntsperger, David, Cameron, Glenn, Zucker, Arthur, Warkentin, Tris, Peran, Ludovic, Giang, Minh, Ghahramani, Zoubin, Farabet, Clément, Kavukcuoglu, Koray, Hassabis, Demis, Hadsell, Raia, Teh, Yee Whye, de Frietas, Nando
We introduce RecurrentGemma, a family of open language models which uses Google's novel Griffin architecture. Griffin combines linear recurrences with local attention to achieve excellent performance on language. It has a fixed-sized state, which red
Externí odkaz:
http://arxiv.org/abs/2404.07839
Autor:
Gemma Team, Mesnard, Thomas, Hardin, Cassidy, Dadashi, Robert, Bhupatiraju, Surya, Pathak, Shreya, Sifre, Laurent, Rivière, Morgane, Kale, Mihir Sanjay, Love, Juliette, Tafti, Pouya, Hussenot, Léonard, Sessa, Pier Giuseppe, Chowdhery, Aakanksha, Roberts, Adam, Barua, Aditya, Botev, Alex, Castro-Ros, Alex, Slone, Ambrose, Héliou, Amélie, Tacchetti, Andrea, Bulanova, Anna, Paterson, Antonia, Tsai, Beth, Shahriari, Bobak, Lan, Charline Le, Choquette-Choo, Christopher A., Crepy, Clément, Cer, Daniel, Ippolito, Daphne, Reid, David, Buchatskaya, Elena, Ni, Eric, Noland, Eric, Yan, Geng, Tucker, George, Muraru, George-Christian, Rozhdestvenskiy, Grigory, Michalewski, Henryk, Tenney, Ian, Grishchenko, Ivan, Austin, Jacob, Keeling, James, Labanowski, Jane, Lespiau, Jean-Baptiste, Stanway, Jeff, Brennan, Jenny, Chen, Jeremy, Ferret, Johan, Chiu, Justin, Mao-Jones, Justin, Lee, Katherine, Yu, Kathy, Millican, Katie, Sjoesund, Lars Lowe, Lee, Lisa, Dixon, Lucas, Reid, Machel, Mikuła, Maciej, Wirth, Mateo, Sharman, Michael, Chinaev, Nikolai, Thain, Nithum, Bachem, Olivier, Chang, Oscar, Wahltinez, Oscar, Bailey, Paige, Michel, Paul, Yotov, Petko, Chaabouni, Rahma, Comanescu, Ramona, Jana, Reena, Anil, Rohan, McIlroy, Ross, Liu, Ruibo, Mullins, Ryan, Smith, Samuel L, Borgeaud, Sebastian, Girgin, Sertan, Douglas, Sholto, Pandya, Shree, Shakeri, Siamak, De, Soham, Klimenko, Ted, Hennigan, Tom, Feinberg, Vlad, Stokowiec, Wojciech, Chen, Yu-hui, Ahmed, Zafarali, Gong, Zhitao, Warkentin, Tris, Peran, Ludovic, Giang, Minh, Farabet, Clément, Vinyals, Oriol, Dean, Jeff, Kavukcuoglu, Koray, Hassabis, Demis, Ghahramani, Zoubin, Eck, Douglas, Barral, Joelle, Pereira, Fernando, Collins, Eli, Joulin, Armand, Fiedel, Noah, Senter, Evan, Andreev, Alek, Kenealy, Kathleen
This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models. Gemma models demonstrate strong performance across academic benchmarks for language understanding,
Externí odkaz:
http://arxiv.org/abs/2403.08295