一种面向文化遗产的包容性轻量级联邦持续学习方法
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人工智能可通过大规模检索和分析数字化馆藏，为文化遗产和数字人文提供支持。然而，文化遗产数据常分布于不同机构，受所有权和访问限制约束，并会随时间持续演变。联邦持续学习（FCL）很适合这一场景，因为它使模型能够在不共享原始馆藏的情况下，从分布式和顺序性数据中学习。本文提出……
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An Inclusive and Lightweight Approach to Federated Continual Learning for Cultural Heritage
Artificial intelligence can support cultural heritage and digital humanities through large-scale retrieval and analysis of digitized collections. However, cultural heritage data are often distributed across institutions, constrained by ownership and access restrictions, and continuously evolving over time. Federated Continual Learning (FCL) is well suited to this setting, as it enables models to learn from distributed and sequential data without sharing raw collections. In this paper, we propose…
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- 01arXiv · AI 文旅预印本原文
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