kitan-liyah/legal_eval
Negation Blind Spots in Legal AI: A Hands-On Evaluation 1. The Blind Spot: Why "Not" Changes Everything While building a legal AI copilot, I kept running into the same dangerous failure mode: if a user asked, "Is the vendor liable for damages?", the system would confidently retrieve and rank a clause stating the vendor is not liable. To a standard AI retriever, "liable" and "not liable" look almost identical. They share the same keywords and occupy the same space… See the full description on the dataset page: https://huggingface.co/datasets/kitan-liyah/legal_eval.
| Author / organization | kitan-liyah |
|---|---|
| Downloads | 0 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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- 16 Oct 2026 Description: none → Negation Blind Spots in Legal AI: A Hands-On Evaluation 1. The Blind Spot: Why "Not" Changes Everything While building a legal AI copilot, I kept running into the same dangerous failure mode: if a user asked, "Is the vendor liable for damag
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