Gender
Datasets
All datasets matching “Gender”md_gender_biasMachine learning models are trained to find patterns in data.
NLP models can inadvertently learn socially undesirable patterns when training on gender biased text.
In this work, we propose a general framework that decomposes gender bias in text along several pragmatic and semantic dimensions:
bias from the gender of the person being spoken about, bias from the gender of the person being spoken to, and bias from the gender of the speaker.
Using this fine-grained framework, we automatically annotate eight large scale datasets with gender information.
In addition, we collect a novel, crowdsourced evaluation benchmark of utterance-level gender rewrites.
Distinguishing between gender bias along multiple dimensions is important, as it enables us to train finer-grained gender bias classifiers.
We show our classifiers prove valuable for a variety of important applications, such as controlling for gender bias in generative models,
detecting gender bias in arbitrary text, and shed light on offensive language in terms of genderedness.Face-Gender-Swap
Dataset Card for "Face-Gender-Swap"
More Information needed
common-voice-17-en-age-gender-accentgender-by-name
Dataset Card for "Gender-by-Name"
This dataset attributes first names to genders, giving counts and probabilities. It combines open-source government data from the US, UK, Canada, and Australia. The dataset is taken from UCI Machine Learning Repository
Dataset Information
This dataset combines raw counts for first/given names of male and female babies in those time periods, and then calculates a probability for a name given the aggregate count. Source datasets are from… See the full description on the dataset page: https://huggingface.co/datasets/erickrribeiro/gender-by-name.GenderVL-Bench
GenderVL-Bench
GenderVL-Bench is a compact vision-language benchmark for evaluating how Vision-Language Models (VLMs) interpret gender-related representations across different occupations.
Dataset
108 images
12 occupations
9 images per occupation
Format: JPEG / ImageFolder
Split: train
Usage
from datasets import load_dataset
dataset = load_dataset("suparnojit/GenderVL-Bench")
Citation
@dataset{sarkar2026gendervlbench,
author… See the full description on the dataset page: https://huggingface.co/datasets/suparnojit/GenderVL-Bench.common-voice-17-en-age-gender