火海
发表于 2025-3-23 09:54:49
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不要不诚实
发表于 2025-3-23 16:45:53
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推迟
发表于 2025-3-23 21:05:21
DT-Anon: Decision Tree Target-Driven Anonymizationarn from the anonymized data. The basic idea of our approach is to perform the anonymization process on partitions produced by a decision tree driven by the target of the classification task. Each partition is then independently anonymized, to limit the impact of anonymization on the attributes and
TAG
发表于 2025-3-24 00:45:11
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gregarious
发表于 2025-3-24 02:32:22
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杀虫剂
发表于 2025-3-24 06:33:41
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SIT
发表于 2025-3-24 11:52:03
ALERT: A Framework for Efficient Extraction of Attack Techniques from Cyber Threat Intelligence Repoel cybersecurity framework which leverages active learning strategies in conjunction with an LLM. This approach dynamically selects the most informative instances for annotation, thereby achieving comparable performance with a significantly smaller dataset. By prioritizing the annotation of samples
赦免
发表于 2025-3-24 18:29:34
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Presbyopia
发表于 2025-3-24 19:02:18
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推迟
发表于 2025-3-25 01:22:43
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