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PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Fuente: arXiv
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Bibliographic Details
Main Authors: Hou, Charlie, Shrivastava, Akshat, Zhan, Hongyuan, Conway, Rylan, Le, Trang, Sagar, Adithya, Fanti, Giulia, Lazar, Daniel
Format: Preprint
Published: 2024
Subjects:
Machine Learning
Artificial Intelligence
Computation and Language
Cryptography and Security
Distributed, Parallel, and Cluster Computing
Online Access:
Acceder al recurso
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