{"url":"/dataset/flickr30k-20-nc-1k-test","name":"Flickr30K-Noisy","full_name":"Flickr-30K with 20% of Noisy Correspondence","description_markdown":"This dataset, based on Flickr30K, is introduced in *Learning with Noisy Correspondence for Cross-modal Matching*. 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nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/recon-enhancing-true-correspondence-1","title":"ReCon: Enhancing True Correspondence Discrimination through Relation Consistency for Robust Noisy Correspondence Learning","date":"2025-02-27","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":3,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/ugncl-uncertainty-guided-noisy-correspondence","title":"UGNCL: Uncertainty-Guided Noisy Correspondence Learning for Efficient Cross-Modal Matching","date":"2024-07-11","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/mitigating-noisy-correspondence-by","title":"Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning","date":"2024-05-27","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":4,"samples_unverified":2,"pointer_only_for_licence":6,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-with-noisy-correspondence","title":"Learning with Noisy Correspondence","date":"2024-04-13","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/cross-modal-retrieval-with-noisy","title":"Cross-modal Retrieval with Noisy Correspondence via Consistency Refining and Mining","date":"2024-03-25","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/nac-mitigating-noisy-correspondence-in-cross","title":"NAC: Mitigating Noisy Correspondence in Cross-Modal Matching Via Neighbor Auxiliary Corrector","date":"2024-03-18","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/repair-rank-correlation-and-noisy-pair-half","title":"REPAIR: Rank Correlation and Noisy Pair Half-replacing with Memory for Noisy Correspondence","date":"2024-03-13","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/learning-to-rematch-mismatched-pairs-for","title":"Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval","date":"2024-03-08","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":8,"samples_unverified":2,"pointer_only_for_licence":10,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/noisy-correspondence-learning-with-self","title":"Noisy Correspondence Learning with Self-Reinforcing Errors Mitigation","date":"2023-12-27","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/cross-modal-active-complementary-learning-1","title":"Cross-modal Active Complementary Learning with Self-refining Correspondence","date":"2023-10-26","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":28,"samples_ran":23,"samples_unverified":5,"pointer_only_for_licence":28,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-from-noisy-correspondence-with-tri","title":"Learning From Noisy Correspondence With Tri-Partition for Cross-Modal Matching","date":"2023-09-22","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/noisy-correspondence-learning-with-meta","title":"Noisy Correspondence Learning with Meta Similarity Correction","date":"2023-04-13","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/bicro-noisy-correspondence-rectification-for","title":"BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistency","date":"2023-03-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":9,"samples_unverified":2,"pointer_only_for_licence":11,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/cross-modal-retrieval-with-partially","title":"Cross-Modal Retrieval with Partially Mismatched Pairs","date":"2023-02-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/deep-evidential-learning-with-noisy","title":"Deep Evidential Learning with Noisy Correspondence for Cross-Modal Retrieval","date":"2022-10-10","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-with-noisy-correspondence-for-cross","title":"Learning with Noisy Correspondence for Cross-modal Matching","date":"2021-12-01","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":62,"samples_ran":49,"samples_unverified":13,"pointer_only_for_licence":55,"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."}