{"url":"/dataset/entigen","name":"ENTIGEN","full_name":"Ethical NaTural Language Interventions in Text-to-Image GENeration","description_markdown":"**ENTIGEN** is a benchmark dataset to evaluate the change in image generations conditional on ethical interventions across three social axes -- gender, skin color, and culture. It contains 246 prompts based on an attribute set containing diverse professions, objects, and cultural scenarios.","description_withheld":null,"homepage":"https://github.com/Hritikbansal/entigen_emnlp","introduced_date":"2022-10-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/how-well-can-text-to-image-generative-models","title":"How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?","first_author":"Hritik Bansal","url":null},"license":{"name":"MIT license","url":"https://github.com/Hritikbansal/entigen_emnlp/blob/main/LICENSE"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Image Generation","url":"/task/image-generation","datasets_with_task":"/datasets/task/image-generation"},{"name":"Text-to-Image Generation","url":"/task/text-to-image-generation","datasets_with_task":"/datasets/task/text-to-image-generation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ENTIGEN"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}