{"as_of":"2026-08-12T10:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:07b7b3eac9318f56317ba48b8f7b1479160e39d2a8760095b6576910577f1e4f","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T22:44:41.706967Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2509.07213/citation-record","integrity":"/paper/2509.07213/integrity","json":"/paper/2509.07213/citation-record.json","paper":"/paper/2509.07213"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:45.106005Z","title":"Key statistics for breast cancer","venue":null,"work_id":"d441789e-10db-40e9-8479-7ce636d6abba","year":2025},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:37.653111Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:b8cad13d9f8bd2ce85a030abc2103a297d66d094e6a1db1a675e3263311efa80","observation_id":"7f1c5019-ab49-48a9-bee9-926c54edd163","resolution":{"observed_at":"2026-08-04T22:44:45.108891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.5534","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:44.950885Z","title":"Nicholson, Michael Silverstein, John B","venue":null,"work_id":"de01bace-13e0-4208-97f2-63ff3efb7235","year":1918},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:37.691317Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:780fadfb873aa866df7ce9667663eeaada69b000113fec1f44eb8f56d7a970e5","observation_id":"0071a102-c5b3-4187-b9a5-5697b2c445e1","resolution":{"observed_at":"2026-08-04T22:44:44.955406Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.ejca.2010.02.015","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group.Eur J Cancer, 46(8):1296–1316, 2010","venue":"European Journal of Cancer","work_id":"5c51fa1e-2668-4cb7-92c4-cb5f2b88e86a","year":2010},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:37.722438Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:af4f4434cf560acb820826745ff90cb9f8a9a0edfc7ecd443dad4155641eb817","observation_id":"8aca90f0-2b3a-417a-adf5-71607323db70","resolution":{"observed_at":"2026-08-04T22:44:43.204294Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.7326/0003-4819-138-3-200302040-00008","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Carney, Diana L","venue":"Annals of Internal Medicine","work_id":"a9bf35b9-6c5d-48f9-ae1a-a00f2d4cbd66","year":2003},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:37.839781Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:0806f0db9a49d68262ce4b6eb0e4b6b06040c78f6892614dffaba4f5eace2c36","observation_id":"35558998-884c-4d3e-993f-ba5553ddab6c","resolution":{"observed_at":"2026-08-04T22:44:43.085101Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s00330-024-10740-5","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Fuchsjäger, Paola Clauser, and Ritse M","venue":"European Radiology","work_id":"113d745a-7972-47c4-95ca-1876420539b3","year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:37.891339Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:46a85dda38bc0578cf014bb1afb4e2dae322e5d8fc27e89d732ae4e2f16e9ce1","observation_id":"a1affb3d-05b6-47dd-a1f6-6542da93e7da","resolution":{"observed_at":"2026-08-04T22:44:42.950393Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s13244-018-0636-z","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Trimboli, Alexandra Athanasiou, and et al","venue":"Insights into Imaging","work_id":"c6641171-e1ea-4cbf-a69e-212a4b9d4392","year":2018},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:37.961486Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:a9b84c619cf566f9fa9a3807ee26a1cb10dfb1c4b0e971be343b2b1346558e47","observation_id":"a6171d77-bd9a-40c5-b896-1cfe7f711b30","resolution":{"observed_at":"2026-08-04T22:44:42.841815Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/healthcare10040729","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Healthcare","work_id":"fae6b8f7-026a-497a-9b24-113caa79ff4a","year":2022},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:37.993229Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:91f12a653282a24e8fc2a89a5d1bf567c8ab9624a67097817782a55e678c152e","observation_id":"196c7150-f5d9-44f3-a150-178cd0fa8bc1","resolution":{"observed_at":"2026-08-04T22:44:42.732188Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.097144Z","title":"Breast ultrasound tumor classification using a hybrid multitask cnn-transformer network","venue":null,"work_id":"2e736ce0-8a14-450e-bf50-74c83e7f37ef","year":2023},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.059817Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:9d846770e9efd7582695a3fd4a8506fa877a33aa1c6805382d9077b896277895","observation_id":"04eb58d2-b9f2-4c5d-8061-d82472c2df05","resolution":{"observed_at":"2026-08-04T22:44:45.100302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.078399Z","title":"D’Orsi, Edward A","venue":null,"work_id":"af7c67d7-d9a8-4323-acf3-79aae78b18d4","year":null},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.141855Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:ac8651c5912bd172925b93981ce0c8c4e10cbba034e7104a6243698469479004","observation_id":"5f4c37a1-5867-44e2-bb9e-41f0a087f54e","resolution":{"observed_at":"2026-08-04T22:44:45.081610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2022.96361","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:44.936694Z","title":"Ultrasound radiomics in personalized breast management: Current status and future prospects.Frontiers in Oncology, 12:963612, 2022","venue":null,"work_id":"b50cebc4-947a-4046-acac-24a493730265","year":2022},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.236200Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:f8f44090bda0e98e522f7c262679839cc28bcb7406c0c391063999e4dde684f5","observation_id":"9b389d8d-7592-4aa1-bf61-b6ec4f10b6bb","resolution":{"observed_at":"2026-08-04T22:44:44.941426Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2006.87709","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:44.859776Z","title":"Alison Noble and Dounia Boukerroui","venue":null,"work_id":"fca8905e-aeac-4b0f-9d8c-a6001e842de8","year":2006},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.304531Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:84afe4fc2354391c5dcd68e60c79e85776cfbef7401d01a7ced79594242564af","observation_id":"84d70892-62a0-4047-bef2-8ba94a83c2e7","resolution":{"observed_at":"2026-08-04T22:44:44.896331Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:38.372320Z","title":"U-net: Convolutional networks for biomedical image segmentation","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.372320Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:272725c83552375e72a9f21494d005796e6c741acd01013a76c92a975ddb463f","observation_id":"b970adb3-2bc3-4855-8e84-efa4b7e3224b","resolution":{"observed_at":"2026-08-04T22:44:38.372320Z","resolver_source":null,"status":"malformed_identifier"},"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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:38.442856Z","title":"Unet++: A nested u-net architecture for medical image segmentation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.442856Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:8c491626715c8dff3cb327bd43658e3c5b63825f3c6dda67a576e0bd668513da","observation_id":"de1c9ed7-2b96-42d2-9a5b-1e6449219a78","resolution":{"observed_at":"2026-08-04T22:44:38.442856Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:38.480963Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.480963Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:ceaf91f04e6fc0c7079e45f358d2522430a1cb48a3501e12b41f2bfcf166708b","observation_id":"16592530-9a5e-411a-ae8c-53686b1732d4","resolution":{"observed_at":"2026-08-04T22:44:38.480963Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:38.548114Z","title":"Weinberger","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.548114Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:8c62e818fa061187042b9d148040454d3c5abdd25789e25e1239a5e7b990efe2","observation_id":"855433cb-6080-41ff-82bd-8d9da15f8c77","resolution":{"observed_at":"2026-08-04T22:44:38.548114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.03999","last_updated":"2018-05-20T23:33:30Z","snapshot_observed_at":"2026-07-06T06:32:53.966022Z","submitted_at":"2018-04-11T14:13:03Z","title":"Attention U-Net: Learning Where to Look for the Pancreas","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.03999","snapshot_observed_at":"2026-08-04T22:44:38.563597Z","title":"Hammerla, Bernhard Kainz, Ben Glocker, and Daniel Rueckert","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.563597Z"},"links":{"cited_paper":"/paper/1804.03999","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:2f6300851208110db082342bfa7c4ed35bd17f7e7733c33954786b228f6d9330","observation_id":"a697b47b-3bfd-413d-88ce-8a97b48c0c95","resolution":{"observed_at":"2026-08-04T22:44:38.563597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17937","last_updated":"2023-05-29T08:00:54Z","snapshot_observed_at":"2026-08-08T06:44:53.097873Z","submitted_at":"2023-05-29T08:00:54Z","title":"Attention Mechanisms in Medical Image Segmentation: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.17937","snapshot_observed_at":"2026-08-04T22:44:38.627501Z","title":"Attention mechanisms in medical image segmentation: A survey.arXiv preprint arXiv:2305.17937, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.627501Z"},"links":{"cited_paper":"/paper/2305.17937","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:9121e5db32347744a0fd31b8d1769455ab8f03a787fc0a6cca3dc52d22f352b8","observation_id":"67bd04ca-bc92-42d1-9e62-76728e9f1299","resolution":{"observed_at":"2026-08-04T22:44:38.627501Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-10T01:12:16.468283Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-04T22:44:38.697893Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale.arXiv preprint, arXiv:2010.11929, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.697893Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:4524baa557301cf7b20bed0e2f8fcc6f53d46384be730102317a10b223ced04d","observation_id":"3e9b395a-ff9e-407b-856e-9e2e9314290c","resolution":{"observed_at":"2026-08-04T22:44:38.697893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.04306","last_updated":"2021-02-08T16:10:50Z","snapshot_observed_at":"2026-08-10T02:39:10.770770Z","submitted_at":"2021-02-08T16:10:50Z","title":"TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.04306","snapshot_observed_at":"2026-08-04T22:44:38.762982Z","title":"Yuille, and Yuyin Zhou","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.762982Z"},"links":{"cited_paper":"/paper/2102.04306","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:2c997c0af9e60ce6ce91b4e8c1d380249990b1b8a9b75b3f5a718ea3ad1ede15","observation_id":"5b627d81-9dc2-4293-a144-2a10c30226d4","resolution":{"observed_at":"2026-08-04T22:44:38.762982Z","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":"2207.2024","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:44.741522Z","title":"Multi-task breast ultrasound image classifi- cation and segmentation using swin transformer and vmamba models","venue":null,"work_id":"b81bc29e-8c7f-467d-91bd-8d983566c2bf","year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.839387Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:d7f11c64d6d67fecd4a353330953dc88af9e043755663544e3596314bf8d2023","observation_id":"9804822e-e720-4388-8619-942fc5398bbf","resolution":{"observed_at":"2026-08-04T22:44:44.777111Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.058950Z","title":"Breast ultrasound tumor classification using a hybrid multitask cnn-transformer network","venue":null,"work_id":"a8057058-42dd-44ed-821a-ca5c882e334f","year":2023},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.935873Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:c2599b497dd73b3560ab19e4155f1b1de7ada9847cfff8d327addd2656ff0556","observation_id":"68b45300-c9e9-406a-b4e6-e25b3d289f42","resolution":{"observed_at":"2026-08-04T22:44:45.062814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2021.31174","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:44.559349Z","title":"Domain adaptation for medical image analysis: A survey.IEEE Transactions on Biomedical Engineering, 69(3):1173–1185, 2022","venue":null,"work_id":"a9b96997-28e3-412f-9fc0-ecd555b09d0a","year":2022},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.026744Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:b28f1418d14c174052300d39ea8c8f9cd072094aaa61dc2254389ba07d220b0b","observation_id":"7176f03d-0e49-4677-b0b2-e9524a2401d1","resolution":{"observed_at":"2026-08-04T22:44:44.647861Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:39.113244Z","title":"Stan: Small tumor-aware network for breast ultrasound image segmentation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.113244Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:89fda3efef1b2cb92fb4c2e1db9effa514b39cc83617ea095cf7a1c1501451c1","observation_id":"c28540e5-7500-4e02-bec4-0a30426711b1","resolution":{"observed_at":"2026-08-04T22:44:39.113244Z","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":"10.3390/healthcare10112262","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Freer, and Min Xian","venue":"Healthcare","work_id":"f9978222-09ea-4c71-b9b7-2d143cbc2dd8","year":2022},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.174399Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:c9073b5a014506af41ab831f36f367916bf7b19fd1580fa51e1900e72321a1b1","observation_id":"849e01b7-83d2-481b-ae7a-07247d34852a","resolution":{"observed_at":"2026-08-04T22:44:42.610645Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41523-020-00218-9","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:42.412144Z","title":"Incorporating the breast imaging reporting and data system (bi-rads) into deep learning for breast ultrasound.NPJ Breast Cancer, 7:8, 2021","venue":null,"work_id":"4b66ce29-da6d-498e-9df0-080e9e5c90f8","year":2021},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.247851Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:f2a25a388191995f724964a5822c204676c3f5715045f11c08c52b49b777f809","observation_id":"daaeb35a-8181-4635-96f7-9910b50b4aa8","resolution":{"observed_at":"2026-08-04T22:44:42.468745Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/diagnostics12010066","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Incorporating the breast imaging reporting and data system lexicon with a fully convolutional network for malignancy detection on breast ultrasound.Diagnostics, 12(1):66, 2022","venue":"Diagnostics","work_id":"796cf7b1-4045-4515-9058-761435758189","year":2022},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.327319Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:21b34a3768af13b01c055c3598a42c390185c4467049a0bedc5241c174c630e8","observation_id":"c0d1ab6d-de23-4795-8e6c-2797d0482277","resolution":{"observed_at":"2026-08-04T22:44:42.329384Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2017.27434","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:44.277994Z","title":"Anatomically constrained neural networks (acnn): Application to cardiac image enhance- ment and segmentation.IEEE Transactions on Medical Imaging, 2017","venue":null,"work_id":"c269a58a-de7b-4d59-8dc6-5267681268f4","year":2017},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.400362Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:64c43c80a21cca000855d7e88f53c8e6f18949a0e6a388bd0df6ae6ae7648b63","observation_id":"7a5703e7-2d0f-47ce-bbd2-ddaa98973da3","resolution":{"observed_at":"2026-08-04T22:44:44.426978Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:39.534660Z","title":"Boundary loss for highly unbalanced segmentation.Medical Image Analysis, 67:101851, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.534660Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:38267c2700b3c025160731bb70902071c7f5bca1e2d84ee3ccc6d73d478bed25","observation_id":"b20281ea-5b0f-4678-a9dc-0310690191b5","resolution":{"observed_at":"2026-08-04T22:44:39.534660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.10030","last_updated":"2019-04-22T18:55:05Z","snapshot_observed_at":"2026-08-08T02:24:49.924444Z","submitted_at":"2019-04-22T18:55:05Z","title":"Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks","version":1},"cited_work":{"arxiv_id":"1904.10030","doi":null,"metadata_source":"pith","pith_arxiv_id":"1904.10030","snapshot_observed_at":"2026-08-04T22:44:43.992227Z","title":"Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks","venue":"eess.IV","work_id":"e2e2be3a-924a-49f5-92e4-02b5a99a5184","year":2019},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.612893Z"},"links":{"cited_paper":"/paper/1904.10030","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:b2798ed0a665f61f794f358f5059ed0d93e22946d2f1e65cd9a22ec5f79c06d8","observation_id":"5b8fbfb7-c1dc-4cd5-8387-7847b4e733f8","resolution":{"observed_at":"2026-08-04T22:44:44.074476Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.049024Z","title":"Topology-preserving deep image segmentation","venue":null,"work_id":"b2554647-e178-45e5-99c1-8354e3363c36","year":2019},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.672193Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:32b2b81ae7c6376469f559a8437fef31ca0433918677a5dde6ed640e72ba7102","observation_id":"032e75d1-1044-4aec-ab7c-1760af23c948","resolution":{"observed_at":"2026-08-04T22:44:45.052326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2021.10185","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:43.880312Z","title":"High-level prior-based loss functions for medical image segmentation: A survey.Computerized Medical Imaging and Graphics, 88: 101852, 2021","venue":null,"work_id":"be7ea383-b86e-48b6-b0f5-77cd30fc0b27","year":2021},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.769635Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:34dbeba31be7f8867d648f4255f65b448fb1f9bac535ea117a83f8f5c6eac245","observation_id":"0b92e21c-05aa-4e8d-84fd-b66102ad4f0b","resolution":{"observed_at":"2026-08-04T22:44:43.928897Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2002.80427","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:43.728846Z","title":null,"venue":null,"work_id":"20794c21-c6cc-4e68-a89a-ce6c75065e93","year":2002},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.836520Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:c0b2cd101aa8787ed51b8bcb21cc1e781f10ca26aca131ec94e64f68383357bf","observation_id":"46e6f6f2-15f5-44e0-bbd0-e41dbad64ff8","resolution":{"observed_at":"2026-08-04T22:44:43.807018Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.ultrasmedbio.2010.04.003","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A critical review and uniformized representation of statistical distributions modeling the envelope of ultrasonic echoes.Ultrasound in Medicine & Biology, 36(7): 1037–1051, 2010","venue":"Ultrasound in Medicine & Biology","work_id":"2a537723-41f4-4a1d-b18c-062812c4bf6b","year":2010},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.880785Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:f5798cbc71231e92b6c8d10d75f2a70be450570c21896f741e3ba56f859d08ad","observation_id":"cd06c97b-bb09-4172-8042-2a16e06aadc8","resolution":{"observed_at":"2026-08-04T22:44:42.219512Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.039308Z","title":"Texture quantified from ultrasound nakagami parametric images is diagnostically relevant for breast lesions.Scientific Reports, 13:10019,","venue":null,"work_id":"10107987-3520-4d53-9b6e-7c05b4c8b88a","year":null},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:39.977778Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:53cb782dd6e437d6a03cec63cb5b4ae83bf7275579399c4be880bcaaf2998dbb","observation_id":"1070d6cc-eb26-4f62-80cb-befcc043f67a","resolution":{"observed_at":"2026-08-04T22:44:45.042748Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.029358Z","title":"Christensen, Armando Manduca, Seth Ehrenberg, and et al","venue":null,"work_id":"8361c759-2baa-4d2e-9558-78a80a82906b","year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.155255Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:99c9455268c54f4a37f71e137baac105167adb0e5886ec3f993e592c31bc978d","observation_id":"881c4d3e-02ee-42be-bdc2-6e96013e4371","resolution":{"observed_at":"2026-08-04T22:44:45.032486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.02643","last_updated":"2023-04-05T17:59:46Z","snapshot_observed_at":"2026-08-08T05:14:59.435033Z","submitted_at":"2023-04-05T17:59:46Z","title":"Segment Anything","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.02643","snapshot_observed_at":"2026-08-04T22:44:40.242307Z","title":"Segment anything.arXiv preprint arXiv:2304.02643, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.242307Z"},"links":{"cited_paper":"/paper/2304.02643","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:a0248cfd86a328ef1524a3a6a6ce546744313bef16bda2710c4e4be1a84f7e0d","observation_id":"c83401b8-14cf-4b14-af5e-6956402ec606","resolution":{"observed_at":"2026-08-04T22:44:40.242307Z","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":"10.1038/s41598-023-37155-5","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:42.030127Z","title":"URL https://pmc.ncbi.nlm.nih.gov/articles/PMC10285086/","venue":null,"work_id":"debdb1e0-c165-4c1d-8af6-1743f6dd51b0","year":null},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.078890Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:edd5fe2d3805a5bfb9c4e58e4a98561eefeb392039c4cf3008f69942551e96b3","observation_id":"f6319d02-183d-4c27-8eb3-389a3f1761aa","resolution":{"observed_at":"2026-08-04T22:44:42.069581Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05499","last_updated":"2024-07-19T06:00:41Z","snapshot_observed_at":"2026-07-06T15:00:58.804337Z","submitted_at":"2023-03-09T18:52:16Z","title":"Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05499","snapshot_observed_at":"2026-08-04T22:44:40.377169Z","title":"Grounding dino: Marrying dino with grounded pre-training for open-set object detection.arXiv preprint arXiv:2303.05499, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.377169Z"},"links":{"cited_paper":"/paper/2303.05499","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:12bcfeb5e181284444b3af38bd1eeea6ea5272c3daeebe8f966b737316f908cf","observation_id":"e5d0ba69-42fa-4f61-a018-4af36a1ae0b5","resolution":{"observed_at":"2026-08-04T22:44:40.377169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14159","last_updated":"2024-01-25T13:12:09Z","snapshot_observed_at":"2026-07-06T17:20:25.138890Z","submitted_at":"2024-01-25T13:12:09Z","title":"Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.14159","snapshot_observed_at":"2026-08-04T22:44:40.460251Z","title":"Grounded sam: Assembling open-world models for diverse visual tasks.arXiv preprint arXiv:2401.14159, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.460251Z"},"links":{"cited_paper":"/paper/2401.14159","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:66116b336867b53ec11776fa9a4c432ff62f5900da3ef71baeeeeebc4291966d","observation_id":"6d471324-7b38-44aa-9368-f598337fb789","resolution":{"observed_at":"2026-08-04T22:44:40.460251Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.10003","last_updated":"2022-03-30T15:42:46Z","snapshot_observed_at":"2026-07-06T12:20:15.645829Z","submitted_at":"2021-12-18T21:27:19Z","title":"Image Segmentation Using Text and Image Prompts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.10003","snapshot_observed_at":"2026-08-04T22:44:40.316861Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.316861Z"},"links":{"cited_paper":"/paper/2112.10003","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:677cda85c35568b7794a428c930ce36c7bc4fdd2402afebc03fd04f33fe92cf3","observation_id":"2fdcdac2-46b1-46fc-9d6a-d3cee4b3c35f","resolution":{"observed_at":"2026-08-04T22:44:40.316861Z","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":"2026-08-04T22:44:45.009578Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":"c22c9b54-4b63-48c0-bc4c-8cd948a19804","year":2014},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.567173Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:6b5c2203466472530e047a6f939b52d6feb8bab7bc7dfd6b7d1d9ff45f7d14ec","observation_id":"5f2e8e47-0d10-44da-a001-2ef97387981c","resolution":{"observed_at":"2026-08-04T22:44:45.013009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:44.999416Z","title":"Berg, and Tamara L","venue":null,"work_id":"f364e372-c9e4-4a41-b90c-62c762f7f2da","year":2016},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.630731Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:d20b7b8b7cfc28984d0c4ee5e4bc2452fbd5d3ad7180660c2902e321655c011c","observation_id":"d67bcf84-30a4-45a5-a1df-fa40924b189e","resolution":{"observed_at":"2026-08-04T22:44:45.002420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.019748Z","title":null,"venue":null,"work_id":"96efa209-4691-41fe-91a0-a1b25db73684","year":2022},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.516971Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:f1d2940fb8742d24ce2eb720f57af6c409373d81649a6d2f4244e08c62c65457","observation_id":"d9e00545-0bd5-4e9c-88aa-1f02a8d3c855","resolution":{"observed_at":"2026-08-04T22:44:45.022982Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14837","last_updated":"2024-04-23T08:43:32Z","snapshot_observed_at":"2026-08-10T11:05:39.308627Z","submitted_at":"2024-04-23T08:43:32Z","title":"Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images","version":1},"cited_work":{"arxiv_id":"2404.14837","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.14837","snapshot_observed_at":"2026-08-04T22:44:43.584573Z","title":"Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images","venue":"eess.IV","work_id":"0da891a0-d613-40d5-8d13-2b668fc98a09","year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.765157Z"},"links":{"cited_paper":"/paper/2404.14837","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:150fc1c270cfe89e84bc7624a500fe7ca762a61f086deb4fd3d636109a87971a","observation_id":"632e0e1b-2f72-4bb6-8444-2688c0225870","resolution":{"observed_at":"2026-08-04T22:44:43.621836Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:40.828977Z","title":"Segment anything in medical images.Nature Communications, 15(1):1022, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.828977Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:df7e197db94dd57fd070f68af0382a73a29002077860848367573765c67ef2c5","observation_id":"7c478436-05ff-4930-be44-002c0cb0c004","resolution":{"observed_at":"2026-08-04T22:44:40.828977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.14660","last_updated":"2024-01-17T14:42:40Z","snapshot_observed_at":"2026-07-06T15:21:04.733820Z","submitted_at":"2023-04-28T07:23:31Z","title":"Segment Anything Model for Medical Images?","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.14660","snapshot_observed_at":"2026-08-04T22:44:40.684395Z","title":"Segment anything model for medical images?arXiv preprint arXiv:2304.14660, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.684395Z"},"links":{"cited_paper":"/paper/2304.14660","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:a63d9951ecf4d42269e0f22be558841803a66a2f5c6422c3ee1d24511d70eb1d","observation_id":"7d6962ec-1fe8-4464-9b03-dc75637974f6","resolution":{"observed_at":"2026-08-04T22:44:40.684395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05530","last_updated":"2024-12-07T04:10:37Z","snapshot_observed_at":"2026-08-11T20:35:43.771036Z","submitted_at":"2024-12-07T04:10:37Z","title":"CLIP-TNseg: A Multi-Modal Hybrid Framework for Thyroid Nodule Segmentation in Ultrasound Images","version":1},"cited_work":{"arxiv_id":"2412.05530","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.05530","snapshot_observed_at":"2026-08-04T22:44:43.425789Z","title":"CLIP-TNseg: A Multi-Modal Hybrid Framework for Thyroid Nodule Segmentation in Ultrasound Images","venue":"cs.CV","work_id":"d75e695f-8c9c-4de9-a00a-bfc6251000b1","year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.969400Z"},"links":{"cited_paper":"/paper/2412.05530","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:b3a06c9f629204476b475b78e8dfe75b08f59e10c75f21de92a32f51b4081010","observation_id":"3aac232b-4168-4ea3-8dab-0063e2d57c6f","resolution":{"observed_at":"2026-08-04T22:44:43.502960Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.15949","last_updated":"2025-03-20T08:46:24Z","snapshot_observed_at":"2026-08-07T16:49:46.533753Z","submitted_at":"2025-03-20T08:46:24Z","title":"CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention","version":1},"cited_work":{"arxiv_id":"2503.15949","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.15949","snapshot_observed_at":"2026-08-04T22:44:43.294807Z","title":"CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention","venue":"cs.CV","work_id":"26176cae-31b2-43ac-bca1-1ea6e3d28c7d","year":2025},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:41.036090Z"},"links":{"cited_paper":"/paper/2503.15949","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:990357afc43627099a24ccd33cc5b388dfa94750aa185e34bbd02ccef842a200","observation_id":"60e56f06-ab46-4c2b-9575-f1c5401ba347","resolution":{"observed_at":"2026-08-04T22:44:43.345666Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.13785","last_updated":"2023-10-17T12:24:24Z","snapshot_observed_at":"2026-08-11T08:24:41.442941Z","submitted_at":"2023-04-26T19:05:34Z","title":"Customized Segment Anything Model for Medical Image Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.13785","snapshot_observed_at":"2026-08-04T22:44:40.886849Z","title":"Customized segment anything model for medical image segmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:40.886849Z"},"links":{"cited_paper":"/paper/2304.13785","citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:d006e1137064175f0de9c8f0480caf19b4d1f917041bbee681dea0636bc79b39","observation_id":"6a82f5ef-4a3f-4f29-8866-b4ea9c542007","resolution":{"observed_at":"2026-08-04T22:44:40.886849Z","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":"2026-08-04T22:44:44.990441Z","title":null,"venue":null,"work_id":"6acd3b0b-83b8-41ec-b387-81d350367bfa","year":2019},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:41.319747Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:d4a6d043fdfca587eaf7fc1ac6958ce1e4e22aac8b359c7658f7ecc69bd20c71","observation_id":"fddd2b7e-7f4e-432e-aa55-b28dbd7c0221","resolution":{"observed_at":"2026-08-04T22:44:44.993465Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:44.980101Z","title":"Sanity checks for saliency maps","venue":null,"work_id":"a113f06c-5cb8-483d-9255-a9f2fdf41008","year":2018},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:41.471656Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:a63db8357175ea2bfc9746a2cc8913fbd7b3a565bb309c6421094bf74d4a3f24","observation_id":"067e4770-d1e4-45bd-b322-3ede08a8148e","resolution":{"observed_at":"2026-08-04T22:44:44.983911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:41.155155Z","title":"Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:41.155155Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:ed8562aceb4869bc54cd54f2a67f3926326de83f9509a56ddef1a8e6d554d616","observation_id":"efdf56e0-2084-4126-9cc7-31aca5a4f519","resolution":{"observed_at":"2026-08-04T22:44:41.155155Z","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":"10.1609/aaai.v39i5.3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T22:44:41.857325Z","title":"U-kan makes strong backbone for medical image segmentation and generation","venue":null,"work_id":"bd69d402-72d5-421a-8ad7-f1a9eee43ccd","year":2025},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:41.636980Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:7c44ab8ecd256200b2f880c8c4bdd5c8bf216088e4f4d7ace77c4ebbd0bd7c80","observation_id":"5e565988-4261-4cb7-a446-d076e6acd064","resolution":{"observed_at":"2026-08-04T22:44:41.933844Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:44.961752Z","title":"Anatosegnet: Anatomy based cnn-transformer network for enhanced breast ultrasound image segmentation","venue":null,"work_id":"76ece076-6bfd-49e0-b7c4-7fd872f1dded","year":2025},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:41.706967Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:dacf2519e7ab392b9a063cacac61ce1a6709c8bc521acd812381e1ba5e593e58","observation_id":"d41d4358-9e8f-4044-8e5b-eadd0b9d8156","resolution":{"observed_at":"2026-08-04T22:44:44.965092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:44.971119Z","title":"Curated benchmark dataset for ultrasound based breast lesion analysis.Scientific Data, 11(1):148, 2024","venue":null,"work_id":"0c12900c-2e1f-4dd3-9eaf-1d3f2c8bcae9","year":2024},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:41.590030Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:8920b05c114f20601a1104ac63ec7ac086600533c91d75c4b732ad1453d79dd7","observation_id":"133ac89a-eb74-4239-bbcc-ed707c2b0b69","resolution":{"observed_at":"2026-08-04T22:44:44.974195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.068615Z","title":"URL https://www.acr.org/Clinical-Resources/Clinical-Tools-and-Reference/ Reporting-and-Data-Systems/BI-RADS","venue":null,"work_id":"bad3e4d5-c3d0-4f5f-af4a-cc9bc54a4a6e","year":null},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.202365Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:48bdcd3c4d8134751348a434b40e5be3ebd30fe29729fa59ebef85dea1684818","observation_id":"2fa66358-26b6-4c81-88df-914354d38c01","resolution":{"observed_at":"2026-08-04T22:44:45.071970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T22:44:45.088182Z","title":"ISBN 978-3-031-43901-8","venue":null,"work_id":"45d96832-e259-4dbb-a27f-5046cab05b94","year":null},"citing_paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-04T22:44:38.102162Z"},"links":{"citing_paper":"/paper/2509.07213"},"observation_digest":"sha256:18ae070541dbf86fa35331738414044d76e2db97b0985b1983f0a502010d5edf","observation_id":"7f2f6f2f-c7d0-4c67-a26f-659cfd42123b","resolution":{"observed_at":"2026-08-04T22:44:45.091410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.07213","last_updated":"2025-09-08T20:45:55Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T17:24:35.000217Z","submitted_at":"2025-09-08T20:45:55Z","title":"XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":1,"metadata_mismatch":6,"parse_uncertain":0,"unresolved":19,"verified_exact":17,"verified_fuzzy":14},"total_outbound_references":57},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2509.07213."}