{"url":"/dataset/genecis","name":"GeneCIS","full_name":null,"description_markdown":"GeneCIS benchmark is designed for measuring models’ ability to adapt to a range of similarity conditions, which is zero-shot evaluation only.","description_withheld":null,"homepage":"https://sgvaze.github.io/genecis","introduced_date":"2023-06-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/genecis-a-benchmark-for-general-conditional-1","title":"GeneCIS: A Benchmark for General Conditional Image Similarity","first_author":"Sagar Vaze","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Zero-Shot Composed Image Retrieval (ZS-CIR)","url":"/task/zero-shot-composed-image-retrieval-zs-cir","datasets_with_task":"/datasets/task/zero-shot-composed-image-retrieval-zs-cir"},{"name":"Zero-shot Composed Person Retrieval","url":"/task/zero-shot-composed-person-retrieval","datasets_with_task":"/datasets/task/zero-shot-composed-person-retrieval"}],"languages":[],"variants":["GeneCIS"],"data_loaders":[],"num_papers_in_archive":16,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/zero-shot-composed-image-retrieval-zs-cir-on-11","task":"Zero-Shot Composed Image Retrieval (ZS-CIR)","dataset_variant":"GeneCIS","rows":11,"metrics":[" A-R@1","A-R@1"],"first_row_in_archive_order":{"model":"OSrCIR (CLIP G/14)","paper":"/paper/reason-before-retrieve-one-stage-reflective","metrics":{" A-R@1":"19.6"},"code_links":[{"title":"Pter61/osrcir","url":"https://github.com/Pter61/osrcir"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/reason-before-retrieve-one-stage-reflective","title":"Reason-before-Retrieve: One-Stage Reflective Chain-of-Thoughts for Training-Free Zero-Shot Composed Image Retrieval","date":"2024-12-15","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/language-only-efficient-training-of-zero-shot","title":"Language-only Efficient Training of Zero-shot Composed Image Retrieval","date":"2023-12-04","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":3,"samples_unverified":5,"pointer_only_for_licence":8,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/vision-by-language-for-training-free","title":"Vision-by-Language for Training-Free Compositional Image Retrieval","date":"2023-10-13","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":4,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/context-i2w-mapping-images-to-context","title":"Context-I2W: Mapping Images to Context-dependent Words for Accurate Zero-Shot Composed Image Retrieval","date":"2023-09-28","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/zero-shot-composed-image-retrieval-with","title":"Zero-Shot Composed Image Retrieval with Textual Inversion","date":"2023-03-27","rows_on_this_dataset":2,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":17,"samples_ran":8,"samples_unverified":9,"pointer_only_for_licence":8,"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."}