Copertina

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Dettagli Bibliografici
Autori principali: Sinha, Amer, Mesnard, Thomas, McKenna, Ryan, Liu, Daogao, Choquette-Choo, Christopher A., Huang, Yangsibo, Yu, Da, Kaissis, George, Charles, Zachary, Liu, Ruibo, Chua, Lynn, Kamath, Pritish, Manurangsi, Pasin, He, Steve, Zhang, Chiyuan, Ghazi, Badih, Pigem, Borja De Balle, Eruvbetine, Prem, Warkentin, Tris, Joulin, Armand, Kumar, Ravi
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Cryptography and Security
Artificial Intelligence
Accesso online:https://arxiv.org/abs/2510.15001
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Sommario:
  • We introduce VaultGemma 1B, a 1 billion parameter model within the Gemma family, fully trained with differential privacy. Pretrained on the identical data mixture used for the Gemma 2 series, VaultGemma 1B represents a significant step forward in privacy-preserving large language models. We openly release this model to the community

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