AmazonScience/FalseReject
FalseReject: A Dataset for Over-Refusal Mitigation in Large Language Models FalseReject is a large-scale dataset designed to mitigate over-refusal behavior in large language models (LLMs)—the tendency to reject safe prompts that merely appear sensitive. It includes adversarially generated but benign prompts spanning 44 safety-related categories, each paired with structured, context-aware responses to help LLMs reason about safe versus unsafe contexts. FalseReject enables… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/FalseReject.
| Author / organization | AmazonScience |
|---|---|
| License (as declared) | cc-by-nc-4.0 |
| Downloads | 845 (as reported by Hugging Face) |
| Likes | 36 |
| Created | 9 May 2025 |
| Last updated at source | 14 May 2025 |
Connected in the knowledge graph
- Flexan/StentorLabs-Stentor-12M-Instruct-GGUFModel · used to train
- mradermacher/Stentor-30M-Instruct-GGUFModel · used to train
- mradermacher/Stentor-30M-Instruct-heretic-safety-defiltered-i1-GGUFModel · used to train
- mradermacher/Stentor-30M-Instruct-heretic-safety-defiltered-GGUFModel · used to train
Recent changes
- 16 Oct 2026 Description: FalseReject: A Dataset for Over-Refusal Mitigation in Large Language Models FalseReject is a large-scale dataset designed to mitigate over-refusal behavior in large language models (LLMs)—the tendency to reject safe prompts that merely appe → FalseReject: A Dataset for Over-Refusal Mitigation in Large Language Models FalseReject is a large-scale dataset designed to mitigate over-refusal behavior in large language models (LLMs)—the tendency to reject safe prompts that merely appe
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