datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
hiring-bias-mitigation-responses
Hiring-bias mitigation — model responses
Every response produced in the mitigation study of LLM hiring decisions: 61 runs,
2,689,200 responses, from 5 open-weight models in English and Ukrainian, at
baseline and under each mitigation family (baseline, embedding, prompt, scrub, sft). Each run is one subset.
All released artifacts: the Hiring Bias Mitigation collection.
Training data of the fine-tuned runs: hiring-bias-mitigation-synthetic-data.
Code, configs, full results and… See the full description on the dataset page: https://huggingface.co/datasets/Stereotypes-in-LLMs/hiring-bias-mitigation-responses.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.task280_stereoset_classification_stereotype_type
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task280_stereoset_classification_stereotype_type
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task280_stereoset_classification_stereotype_type.hiring-analyses-second_model_verification-entask316_crows-pairs_classification_stereotype
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task316_crows-pairs_classification_stereotype
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task316_crows-pairs_classification_stereotype.toxicchat_output-Ukrtask277_stereoset_sentence_generation_stereotype
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task277_stereoset_sentence_generation_stereotype
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task277_stereoset_sentence_generation_stereotype.hiring-analyses-recruiter_guidelines-enNemotron-Safety-Guard-Dataset-v3-Ukr
Dataset Description
This is the localized Ukrainian version of the Nemotron-Safety-Guard-Dataset-v3. This specific repository contains exclusively the English subset of the original dataset, which has been fully translated into Ukrainian using the Lapa (Gemma 3) series of multimodal instructive models.
The original dataset was curated using the CultureGuard pipeline, which culturally adapts and translates content from the English Aegis 2.0 safety dataset. This Ukrainian variant… See the full description on the dataset page: https://huggingface.co/datasets/Stereotypes-in-LLMs/Nemotron-Safety-Guard-Dataset-v3-Ukr.hiring-analyses-ignore_personal_info-enhiring-analyses-recruiter_guidelines-ukhiring-analyses-baseline-enhiring-analyses-reasoning-enhiring-analyses-baseline-ukhiring-analyses-zero_shot_cot-enhiring-analyses-optimized_parameters-enUAlign⚠️ Disclaimer: This dataset contains examples of morally and socially sensitive scenarios, including potentially offensive, harmful, or illegal behavior. It is intended solely for research purposes related to value alignment, cultural analysis, and safety in AI. Use responsibly.
UAlign: LLM Alignment Evaluation Benchmark
This benchmark consists of two test-only subsets adapted into Ukrainian:
ETHICS (Commonsense subset): A binary classification task on ethical acceptability.… See the full description on the dataset page: https://huggingface.co/datasets/Stereotypes-in-LLMs/UAlign.hiring-analyses-reasoning-uktask279_stereoset_classification_stereotype
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task279_stereoset_classification_stereotype
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task279_stereoset_classification_stereotype.hiring-analyses-ignore_personal_info-ukhiring-analyses-optimized_parameters-ukhiring-analyses-second_model_verification-ukStereotype-Elicitation-Prompt-Librarytask317_crows-pairs_classification_stereotype_type
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task317_crows-pairs_classification_stereotype_type
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task317_crows-pairs_classification_stereotype_type.hiring-analyses-zero_shot_cot-uksafety-eval-walledai_Stereotypeflan_combined_task316_crows-pairs_classification_stereotypeflan_combined_task277_stereoset_sentence_generation_stereotypeGBEM-UA
Overview
This dataset was created for the paper “GBEM-UA: Gender Bias Evaluation and Mitigation for Ukrainian Large Language Models” to study gender bias in the "hiring problem" within the Ukrainian language, focusing on how grammatical gender (e.g., feminitive vs. non-feminitive forms) may influence model predictions.
Dataset Structure
Each row includes:
sentence: the candidate description
profession: base profession name
experience: "relevant" or "irrelevant"… See the full description on the dataset page: https://huggingface.co/datasets/Stereotypes-in-LLMs/GBEM-UA.flan_combined_task279_stereoset_classification_stereotype