mlsanityData to 14 Oct 2026

A Study on Question-Answer Dataset for LLM Safety Evaluation with a Focus on Illegal Activities

arXiv 2605.29340 ↗First posted 28 May 2026cs.CLcited by 0

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Abstract (arXiv)

In this paper, we discuss question-answer dataset for LLM safety evaluation, with a focus on illegal activities. Specifically, on the basis of manual analysis of AnswerCarefully, we introduce several additional information, methods for creating question-answer examples, and a rubric for evaluating LLM-generated responses. The outcomes of this study are intended to be shared with the "JAI-Trust" project.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 8 references that are in the map. First posted on arXiv 28 May 2026.

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References · 3

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2024A Survey on LLM-as-a-Judgecited by 1,423
  3. 2019When Choosing Plausible Alternatives, Clever Hans can be Clevercited by 40

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  1. 2025QGuard:Question-based Zero-shot Guard for Multi-modal LLM Safety
  2. 2023ToolQA: A Dataset for LLM Question Answering with External Tools
  3. 2025Evaluating the efficacy of LLM Safety Solutions : The Palit Benchmark Dataset
  4. 2024SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecurity
  5. 2025SafeLawBench: Towards Safe Alignment of Large Language Models
  6. 2023Fake Alignment: Are LLMs Really Aligned Well?
  7. 2024AttackQA: Development and Adoption of a Dataset for Assisting Cybersecurity Operations using Fine-tuned and Open-Source LLMs
  8. 2024How (un)ethical are instruction-centric responses of LLMs? Unveiling the vulnerabilities of safety guardrails to harmful queries