zefang-liu/secqa
SecQA SecQA is a specialized dataset created for the evaluation of Large Language Models (LLMs) in the domain of computer security. It consists of multiple-choice questions, generated using GPT-4 and the Computer Systems Security: Planning for Success textbook, aimed at assessing the understanding and application of LLMs' knowledge in computer security. Dataset Details Dataset Description SecQA is an innovative dataset designed to benchmark… See the full description on the dataset page: https://huggingface.co/datasets/zefang-liu/secqa.
| Author / organization | zefang-liu |
|---|---|
| License (as declared) | cc-by-nc-sa-4.0 |
| Downloads | 8.5K (as reported by Hugging Face) |
| Likes | 12 |
| Created | 20 December 2023 |
| Last updated at source | 16 May 2024 |
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Recent changes
- 17 Oct 2026 Description: SecQA SecQA is a specialized dataset created for the evaluation of Large Language Models (LLMs) in the domain of computer security. It consists of multiple-choice questions, generated using GPT-4 and the Computer Systems Security: Planning → SecQA SecQA is a specialized dataset created for the evaluation of Large Language Models (LLMs) in the domain of computer security. It consists of multiple-choice questions, generated using GPT-4 and the Computer Systems Security: Planning
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Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 19 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.