{"url":"/dataset/mmea-umvm","name":"UMVM","full_name":null,"description_markdown":"We present a further analysis of visual modality incompleteness, benchmarking latest MMEA models on our proposed dataset MMEA-UMVM.\r\n\r\nTo create our **MMEA-UMVM**(uncertainly missing visual modality) datasets, we perform random image dropping on MMEA datasets. Specifically, we randomly discard entity images to achieve varying degrees of visual modality missing, ranging from 0.05 to the maximum $R_{img}$ of the raw datasets with a step of 0.05 or 0.1. \r\nFinally, we get a total number of 97 data split. \r\n\r\nRefer to the following paper for more details: [*Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment*](https://arxiv.org/abs/2307.16210)","description_withheld":null,"homepage":"https://github.com/zjukg/UMAEA","introduced_date":"2023-07-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/rethinking-uncertainly-missing-and-ambiguous","title":"Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment","first_author":"Zhuo Chen","url":null},"license":{"name":"MIT","url":"https://github.com/zjukg/UMAEA/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Graphs","url":"/datasets/modality/graphs"}],"tasks":[{"name":"Knowledge Graphs","url":"/task/knowledge-graphs","datasets_with_task":"/datasets/task/knowledge-graphs"},{"name":"Entity Alignment","url":"/task/entity-alignment","datasets_with_task":"/datasets/task/entity-alignment"},{"name":"Multi-modal Entity Alignment","url":"/task/multi-modal-entity-alignment","datasets_with_task":"/datasets/task/multi-modal-entity-alignment"}],"languages":[{"name":"English","url":"/datasets/language/english"},{"name":"French","url":"/datasets/language/french"},{"name":"Chinese","url":"/datasets/language/chinese"},{"name":"Japanese","url":"/datasets/language/japanese"}],"variants":["UMVM-oea-en-fr","UMVM-oea-en-de","UMVM-oea-d-w-v2","UMVM-oea-d-w-v1","UMVM-dbp-fr-en","UMVM-dbp-ja-en","UMVM-dbp-zh-en","UMVM"],"data_loaders":[{"repo":"https://github.com/zjukg/umaea","url":"https://github.com/zjukg/umaea","frameworks":["pytorch"]}],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multi-modal-entity-alignment-on-umvm-dbp-fr","task":"Multi-modal Entity Alignment","dataset_variant":"UMVM-dbp-fr-en","rows":10,"metrics":["Hits@1"],"first_row_in_archive_order":{"model":"UMAEA (w/o surf)","paper":"/paper/rethinking-uncertainly-missing-and-ambiguous","metrics":{"Hits@1":"0.873"},"code_links":[{"title":"zjukg/umaea","url":"https://github.com/zjukg/umaea"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multi-modal-entity-alignment-on-umvm-dbp-ja","task":"Multi-modal Entity Alignment","dataset_variant":"UMVM-dbp-ja-en","rows":10,"metrics":["Hits@1"],"first_row_in_archive_order":{"model":"UMAEA (w/o surf)","paper":"/paper/rethinking-uncertainly-missing-and-ambiguous","metrics":{"Hits@1":"0.857"},"code_links":[{"title":"zjukg/umaea","url":"https://github.com/zjukg/umaea"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multi-modal-entity-alignment-on-umvm-dbp-zh","task":"Multi-modal Entity Alignment","dataset_variant":"UMVM-dbp-zh-en","rows":10,"metrics":["Hits@1"],"first_row_in_archive_order":{"model":"UMAEA (w/o surf)","paper":"/paper/rethinking-uncertainly-missing-and-ambiguous","metrics":{"Hits@1":"0.856"},"code_links":[{"title":"zjukg/umaea","url":"https://github.com/zjukg/umaea"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/rethinking-uncertainly-missing-and-ambiguous","title":"Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment","date":"2023-07-30","rows_on_this_dataset":6,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":5,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/meaformer-multi-modal-entity-alignment","title":"MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid","date":"2022-12-29","rows_on_this_dataset":6,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":13,"samples_ran":5,"samples_unverified":8,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multi-modal-contrastive-representation","title":"Multi-modal Contrastive Representation Learning for Entity Alignment","date":"2022-09-02","rows_on_this_dataset":6,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":3,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multi-modal-siamese-network-for-entity","title":"Multi-modal Siamese Network for Entity Alignment","date":"2022-08-14","rows_on_this_dataset":6,"code_links":1,"syntology":null},{"paper":"/paper/visual-pivoting-for-unsupervised-entity","title":"Visual Pivoting for (Unsupervised) Entity Alignment","date":"2020-09-28","rows_on_this_dataset":6,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":3,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":46,"samples_ran":16,"samples_unverified":30,"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."}