Stereotypes-in-LLMs/hiring-bias-mitigation-synthetic-data
Hiring-bias mitigation — synthetic training data Semi-synthetic data for training LLMs to make hiring decisions that do not depend on a protected attribute (military status, gender, religion), in English and Ukrainian. Real inputs, synthetic labels. CVs and job descriptions are real, anonymised postings from the Djinni Recruitment Dataset (MIT). Decisions and rationales were written by the teacher model Qwen/Qwen3.5-122B-A10B-GPTQ-Int4. Code and results:… See the full description on the dataset page: https://huggingface.co/datasets/Stereotypes-in-LLMs/hiring-bias-mitigation-synthetic-data.
| Author / organization | Stereotypes-in-LLMs |
|---|---|
| License (as declared) | mit |
| Downloads | 389 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 19 September 2026 |
| Last updated at source | 23 September 2026 |
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