{"as_of":"2026-08-21T04:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:91335097e4e7c4b458c8616bfe6af66aa7927ea14214c26394826f2116a3eb58","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:10:52.837080Z","state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-30T13:14:51.329289Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-30T13:24:40.594032Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"cited_work":{"arxiv_id":"2411.16421","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.16421","snapshot_observed_at":"2026-06-30T13:24:40.594032Z","title":"Digital typhoon: Long-term satellite image dataset for the spatio-temporal modeling of tropical cyclones.Advances in Neural Information Processing Systems, 36:40623–40636, 2023","venue":null,"work_id":"36d33988-53d1-4979-9970-a0d1757d2317","year":2023},"citing_paper":{"arxiv_id":"2605.24782","last_updated":"2026-06-02T19:00:16Z","snapshot_observed_at":"2026-08-17T12:54:02.386095Z","submitted_at":"2026-05-23T23:51:19Z","title":"The Perception-Physics Paradox: Probing Scientific Alignment with TC-Bench","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-30T13:14:51.329289Z"},"links":{"cited_paper":"/paper/2411.16421","citing_paper":"/paper/2605.24782"},"observation_digest":"sha256:0bfbf572944243b609ae14b61173ac5dc680e49bdb569c5bdb04c566e79a9ef3","observation_id":"8543cac7-5fe7-481f-b64d-3a8a6a6df42e","resolution":{"observed_at":"2026-06-30T13:24:40.595803Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.16421/citation-record","integrity":"/paper/2411.16421/integrity","json":"/paper/2411.16421/citation-record.json","paper":"/paper/2411.16421"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2002.05709","last_updated":"2020-07-01T00:09:08Z","snapshot_observed_at":"2026-08-15T20:49:51.676387Z","submitted_at":"2020-02-13T18:50:45Z","title":"A Simple Framework for Contrastive Learning of Visual Representations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.05709","snapshot_observed_at":"2026-08-12T13:10:52.760572Z","title":null,"venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.760572Z"},"links":{"cited_paper":"/paper/2002.05709","citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:1985d428aeaf69417e8650b1d30e23bbdc5442168417a960cc57b2d5ea508799","observation_id":"1c544b96-4c8c-4603-9814-d078c003a9aa","resolution":{"observed_at":"2026-08-12T13:10:52.760572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.04297","last_updated":"2020-03-09T17:56:49Z","snapshot_observed_at":"2026-07-06T09:03:25.467987Z","submitted_at":"2020-03-09T17:56:49Z","title":"Improved Baselines with Momentum Contrastive Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.04297","snapshot_observed_at":"2026-08-12T13:10:52.765569Z","title":"Girshick, and Kaiming He","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.765569Z"},"links":{"cited_paper":"/paper/2003.04297","citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:60fb7e2155dd8168f0626379f2d48baa8e74436a407692e06385bc32dd39e403","observation_id":"4ce2e96f-0a2c-455b-a3d8-e4b26d09dbf9","resolution":{"observed_at":"2026-08-12T13:10:52.765569Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:53.084273Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale, 2021","venue":null,"work_id":"e6485bf7-0d4c-4834-8a95-5c406d015d28","year":2021},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.770263Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:08f0d6d057d1df9dc33f54219745a01d46990bdb437b9b51ed256686b9c77be6","observation_id":"d2118e0f-373e-40c8-8572-c50325edaa5c","resolution":{"observed_at":"2026-08-12T13:10:53.088892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:53.069577Z","title":"CenterNet: Keypoint triplets for object detection, 2019","venue":null,"work_id":"901e5a9b-a913-4b6e-ae5d-8df851e55853","year":2019},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.774771Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:7d9090a14bd62e1fed55bc8df9be58f2f6a7ab5691701c078a02251e753e1456","observation_id":"b3fc5459-84c3-497b-bc7d-b46fc8bf540b","resolution":{"observed_at":"2026-08-12T13:10:53.074739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:53.056123Z","title":"100 Years of Progress in Tropical Cyclone Research","venue":null,"work_id":"a6206c65-d38f-4dcc-b9f1-2f6a5dbba51d","year":2018},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.779366Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:61e8c1f04c5aa391e8452347a098a33ad60987bcbc6b69ae7ebc6d799e6926fb","observation_id":"52283580-1f24-4c03-bf40-20737fd1a336","resolution":{"observed_at":"2026-08-12T13:10:53.060424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:53.041950Z","title":"Rich feature hierarchies for accurate object detection and semantic segmentation, 2014","venue":null,"work_id":"59ac31e1-c7a3-4939-9c46-ec19511c3893","year":2014},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.784121Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:9ac245c17e5974ddd43156c915e6669b0e3aaff7686a92f4a4195de1be75a09a","observation_id":"7019e304-32f4-47f0-8798-505be929bb74","resolution":{"observed_at":"2026-08-12T13:10:53.046351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.788702Z","title":"Deep residual learning for image recognition, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.788702Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:b2dcb76b2fdbcb8ad73638483c11f7022e6dd0e5fac03d84b04592280e38bd75","observation_id":"78b33e58-1807-42af-b0ad-127a69e3b5bf","resolution":{"observed_at":"2026-08-12T13:10:52.788702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:53.020069Z","title":"Long short-term memory","venue":null,"work_id":"cfb6f782-b1e1-469a-91f6-cc9c4300bf63","year":1997},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.793127Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:c282210ae830b436dd4355dc8958ffcbcfd35979c28f79262cefd80ca47853d0","observation_id":"0f79e435-57ce-4668-85b2-ac76def604e5","resolution":{"observed_at":"2026-08-12T13:10:53.024641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.797246Z","title":"Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.797246Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:d1a6a137ab822e17566dc38636a7ae862f21df895089eb896702252cfcd5bc62","observation_id":"898aa15b-b57c-41fd-8893-17d5b130402f","resolution":{"observed_at":"2026-08-12T13:10:52.797246Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.20783/dias","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.865356Z","title":"Digital Typhoon Dataset V2","venue":null,"work_id":"8335506d-8c82-40f6-bb34-cace6db6aac5","year":null},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.801415Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:b188c88639f48a87fd0c6058b1b034c1258b5ca05b6968993220405eeab44e0f","observation_id":"7dee36e5-8ced-452f-9b0b-a81a7c5c67a6","resolution":{"observed_at":"2026-08-12T13:10:52.870901Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.997407Z","title":"Digital typhoon: Long-term satellite image dataset for the spatio- temporal modeling of tropical cyclones","venue":null,"work_id":"985cf588-5633-494f-b5b6-5fcc11d33cc2","year":2023},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.805794Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:d6e75b4be7267bc47318ac5c31d943d83a03602ffcf00e6f5d34a3aafb49d352","observation_id":"3465392d-d563-4850-a67b-d081e28c9d86","resolution":{"observed_at":"2026-08-12T13:10:53.001933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.984601Z","title":"Knapp and Michael C","venue":null,"work_id":"a6d8429d-eb23-4365-90e4-09c516048e8e","year":2010},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.809829Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:84fc0a5165160c25c6dae20311e175c294b13ddeb259c508fa90fb7a27775fa2","observation_id":"8a2626df-aaa1-4ad8-b334-4dab2dbf5e27","resolution":{"observed_at":"2026-08-12T13:10:52.988638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.971546Z","title":"Knapp, Michael C","venue":null,"work_id":"ba8e8aed-fdd4-49a9-8c12-ac73c8c59466","year":2010},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.814962Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:80340199e57ac7f0a2679e872d6b81c91b38879c4bcd4a319daa7f5505144803","observation_id":"7dce064c-3161-4855-8323-9b2c014e9315","resolution":{"observed_at":"2026-08-12T13:10:52.975673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.957266Z","title":"Operational Use of the Typhoon Intensity Forecasting Scheme Based on SHIPS (TIFS) and Commencement of Five-day Tropical Cyclone Intensity Forecasts","venue":null,"work_id":"96a34520-cb6f-43a2-aed9-4cded21f52d1","year":2019},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.818911Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:a2a2d40db0f118d5d1830faf77f82c605bb022ec6235647e521e4f2c544e5eff","observation_id":"da5cf6d4-18b2-42d2-8330-e8d7fc6f9b92","resolution":{"observed_at":"2026-08-12T13:10:52.962679Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.823900Z","title":"You only look once: Unified, real-time object detection, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.823900Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:240477cae6df97e8696a75c2bbf0133bdb2e572a578021eb5dc6ae5bb3f79ece","observation_id":"405a5c17-2ea6-411e-bc95-6eae6c275bd5","resolution":{"observed_at":"2026-08-12T13:10:52.823900Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.935769Z","title":null,"venue":null,"work_id":"8b091265-936e-4445-890f-44ca6b49b928","year":2019},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.828723Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:86fc538335d20dacbf2b3dcbbb30fbeaa7af5a499b39205a44511930a8bb1371","observation_id":"48bc90c6-5f2a-4846-83e2-4aa01229ec39","resolution":{"observed_at":"2026-08-12T13:10:52.939981Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:10:52.921078Z","title":"U-Net: Convolutional networks for biomedical image segmentation, 2015","venue":null,"work_id":"e053b616-680e-4f7f-bb25-a1369f971c3d","year":2015},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.832747Z"},"links":{"citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:ab418ec2a826fa92699a3ff463e81eb4045e9d2b890692d0d9a228f7eab9718f","observation_id":"7a4c20f5-bce2-4c92-8642-9c2dfda2e4e5","resolution":{"observed_at":"2026-08-12T13:10:52.926397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-08-14T18:53:38.574749Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-08-12T13:10:52.837080Z","title":"Representation learning with contrastive predictive coding","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T13:10:52.837080Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2411.16421"},"observation_digest":"sha256:94b3092d005c44ba6cc9943869e470d0c3622f3c4c91ae8ce2e9a8673ab3cc8f","observation_id":"82b6bf88-b5b9-4e39-9fd1-77dab25a333c","resolution":{"observed_at":"2026-08-12T13:10:52.837080Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.16421","last_updated":"2024-11-25T14:25:39Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-20T18:58:03.318668Z","submitted_at":"2024-11-25T14:25:39Z","title":"Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":10},"total_outbound_references":18},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2411.16421."}