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TechniqueRAG: Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text

Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Main:7 Pages
7 Figures
Bibliography:2 Pages
8 Tables
Appendix:5 Pages
Abstract

Accurately identifying adversarial techniques in security texts is critical for effective cyber defense. However, existing methods face a fundamental trade-off: they either rely on generic models with limited domain precision or require resource-intensive pipelines that depend on large labeled datasets and task-specific optimizations, such as custom hard-negative mining and denoising, resources rarely available in specialized domains.

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