Papers by Dragan Milchevski

3 papers
Multi-Step Generation of Test Specifications using Large Language Models for System-Level Requirements (2025.acl-industry)

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Challenge: System-level testing is a critical phase in the development of large, safety-dependent systems, such as those in the automotive industry.
Approach: They propose an AI-powered assistant to aid users in creating test specifications for system-level requirements.
Outcome: The proposed system reduces the effort required to derive test specifications by 30% in ROUGE-L.
AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports (2024.lrec-main)

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Challenge: Abstract: Natural language processing can help with managing large amounts of unstructured information.
Approach: They propose to annotate a CC-BY-SA-licensed dataset of cyber threat reports . they use named entities, temporal expressions, and cybersecurity-specific concepts .
Outcome: The proposed dataset annotates reports with named entities, temporal expressions, and cybersecurity-specific concepts including implicitly mentioned techniques and tactics.
A Cost-Efficient Modular Sieve for Extracting Product Information from Company Websites (2024.emnlp-industry)

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Challenge: Existing methods for extracting product information are resource-intensive and computationally prohibitive due to website structure differences and numerous non-product pages.
Approach: They propose a modular method that leverages low-cost classification models to filter out company web pages.
Outcome: The proposed method improves on a new dataset of 7000 product and non-product web pages and reduces computational time and costs.

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