{"url":"/dataset/nyctaxi","name":"NYCTaxi","full_name":null,"description_markdown":"Taxi flow data of New York City with grid 20x10.","description_withheld":null,"homepage":"https://github.com/Echo-Ji/ST-SSL_Dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Traffic Prediction","url":"/task/traffic-prediction","datasets_with_task":"/datasets/task/traffic-prediction"}],"languages":[],"variants":["NYCTaxi"],"data_loaders":[],"num_papers_in_archive":12,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/traffic-prediction-on-nyctaxi","task":"Traffic Prediction","dataset_variant":"NYCTaxi","rows":5,"metrics":["MAE @ in","MAE @ out","MAPE (%) @ in","MAPE (%) @ out"],"first_row_in_archive_order":{"model":"ST-SSL","paper":"/paper/spatio-temporal-self-supervised-learning-for","metrics":{"MAE @ in":"11.99","MAE @ out":"9.78","MAPE (%) @ in":"16.38","MAPE (%) @ out":"16.86"},"code_links":[{"title":"echo-ji/st-ssl","url":"https://github.com/echo-ji/st-ssl"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/online-test-time-adaptation-of-spatial","title":"Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting","date":"2024-01-08","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":8,"samples_unverified":1,"pointer_only_for_licence":9,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/spatio-temporal-self-supervised-learning-for","title":"Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction","date":"2022-12-07","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/spatial-temporal-fusion-graph-neural-networks","title":"Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting","date":"2020-12-15","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/adaptive-graph-convolutional-recurrent","title":"Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting","date":"2020-07-06","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":5,"samples_unverified":2,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/spatial-temporal-synchronous-graph","title":"Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting","date":"2020-04-03","rows_on_this_dataset":1,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":16,"samples_ran":13,"samples_unverified":3,"pointer_only_for_licence":10,"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."}