Papers with error-prone process

2 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.
ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery (2026.acl-demo)

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Challenge: a new approach to natural-language research questions requires manual effort to generate an annotation schema and label the corpus.
Approach: They propose a natural-language search tool that takes a question and a corpus to produce a schema and db with a web interface that lets steer and revise the extraction.
Outcome: The proposed model yields outputs that support real-world analysis in law and computational biology.

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