{"as_of":"2026-08-17T02:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a6b71b20a769fe9f205999405d1194cf840c00e66de22272785d6642fab32950","coverage":[{"denominator":19,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T05:54:47.183674Z","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":"2026-08-16T06:30:59.297886+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/2604.17920/citation-record","integrity":"/paper/2604.17920/integrity","json":"/paper/2604.17920/citation-record.json","paper":"/paper/2604.17920"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Maritime Surveillance Finding Dark Ships with Satellites and Artificial Intelli- gence","venue":null,"work_id":"1a88c409-bec8-4bf2-87d0-798f096e252c","year":2024},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:e6855c0d898f5350fecf801564e6fc9902a5cd31e10dd9092dd45ac2698758c7","observation_id":"30e3b1fa-6c61-4cd4-b4d7-8d55bae693d5","resolution":{"observed_at":"2026-05-21T18:35:29.009955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Automatic Ship Detection Based on RetinaNet Us- ing Multi-Resolution Gaofen-3 Imagery","venue":null,"work_id":"2edc4d74-f118-4457-9e16-276fc3e3eeaf","year":2019},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:c7487ce6d1f2f8ca7108d76effd39d65ec05401f8bbf027d5e100ad852fbe15c","observation_id":"37132778-eb37-4482-aa53-f7b191ae17f4","resolution":{"observed_at":"2026-05-21T18:35:29.004029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Data-driven methods for detection of abnormal ship behavior: Progress and trends","venue":null,"work_id":"b051684a-e2e5-430d-a4e2-add1919e009f","year":2023},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:80558c403455086bd476a478b621893e00edf710bd6c1caf1044e4d72ef54ac9","observation_id":"9910eb5b-0795-493a-8b43-603591f8e340","resolution":{"observed_at":"2026-05-21T18:35:28.993713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Ship detection in SAR im- ages based on an improved faster R-CNN","venue":null,"work_id":"c9c4dad1-d07d-4054-9741-c58f390b3af8","year":2017},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:6119a5f61576136777bef8376b549f5db6ed791418eb349953b3f271854ec4b9","observation_id":"18162607-d9dd-490b-a3df-6f22fc5a9d72","resolution":{"observed_at":"2026-05-21T18:35:29.007120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"A Review of Deep-Learning-Based SAR Image Ship Interpreta- tion Technology: The Latest Advances","venue":null,"work_id":"efa2c9ae-af9b-48d1-8521-836925640983","year":2025},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:bee103b19fd95e97fc583e26d2ca41f65385f43d616210b0b339eecc8f30dc8f","observation_id":"09db7e4a-f339-413c-9a0a-c5db5f86dc64","resolution":{"observed_at":"2026-05-21T18:35:29.012735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"LS-SSDD-v1.0: A Deep Learn- ing Dataset Dedicated to Small Ship Detection from Large-Scale Sentinel-1 SAR Images","venue":null,"work_id":"bbba64b2-1fa9-4cb9-b4a0-008d7de64924","year":2020},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:0c6e5483dcc22ff5e89fb0712fda273ce7d849fa271080415cff8af90044b3ce","observation_id":"674afa82-e3c9-4e5e-af8b-bd411dc860b0","resolution":{"observed_at":"2026-05-21T18:35:28.996701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"SAR Ship Detection Dataset (SSDD): Official Release and Comprehensive Data Analysis","venue":null,"work_id":"de37bfe9-df94-4ed8-baa5-f715a202669a","year":2021},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:2be0fd508fbbfffcdf2c49173fcbdda825502500a38c10fca52d2b675d9af948","observation_id":"e8606027-a18f-4ff5-bce9-174b38e12d02","resolution":{"observed_at":"2026-05-21T18:35:29.015672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Segment Anything","venue":null,"work_id":"4df603e1-07cd-4e5a-9815-cb6bb51049c9","year":2023},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:102121b3376f87a7a0bec1b3ebf70c77483da9a1433b70d2c1f390df8024e9a6","observation_id":"ca07dcd2-514c-4bd4-947f-cea5c0a1ba79","resolution":{"observed_at":"2026-05-21T18:35:29.000280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00714","last_updated":"2024-10-28T16:37:57Z","snapshot_observed_at":"2026-07-06T18:55:41.459417Z","submitted_at":"2024-08-01T17:00:08Z","title":"SAM 2: Segment Anything in Images and Videos","version":2},"cited_work":{"arxiv_id":"2408.00714","doi":"10.1038/s41598-025-97590-3","metadata_source":"pith","pith_arxiv_id":"2408.00714","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SAM 2: Segment Anything in Images and Videos","venue":"cs.CV","work_id":"acc13f66-d814-44f9-9688-375688bf2d4a","year":2024},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"cited_paper":"/paper/2408.00714","citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:b4aea01323a4647780e5ad67da9b584b1bed836daa1e765a68a1472ae3b4cd03","observation_id":"05ac9f72-d7bd-4c66-ad53-122e57cc6ee5","resolution":{"observed_at":"2026-05-10T13:56:25.474502Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-05-24T04:24:23.885301+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T04:24:23.885301+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.21722","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"On the Status of Foundation Mod- els for SAR Imagery","venue":null,"work_id":"dfac508f-03cb-4599-a770-fa02298041c0","year":2025},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:4153ec9baa1fce114e0a334463108041e380a56793c2fa7117b9b720f7d108f6","observation_id":"a9772402-601a-410f-855a-c11228a4aa83","resolution":{"observed_at":"2026-05-10T05:56:11.067978Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"SAMSAR: A modified SAM architecture for oceanic ship segmentation of satellite SAR images using CNN-based Cross- Fused Attention","venue":null,"work_id":"8afce46d-bd0e-4595-8ce5-2309e46b7c60","year":2025},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:f409eccf275e5103f47478e29e7f26c001f38e78748a0515a31610de1e8b39dc","observation_id":"d6e5425f-d569-4214-986a-495e9ba6a637","resolution":{"observed_at":"2026-05-21T18:35:28.987257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Tun- ing a SAM-Based Model With Multicognitive Vi- sual Adapter to Remote Sensing Instance Segmen- tation","venue":null,"work_id":"971ec9fb-72a4-4c14-883e-0d62b3193934","year":2025},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:050682393f25f423bc84103bf8e3bd5439e6e932a48fe8250b4769e79f1b3c4b","observation_id":"2444b90d-c22c-452b-ad42-19d8af831332","resolution":{"observed_at":"2026-05-21T18:35:28.990821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Context-Aggregated and SAM-Guided Network for ViT-Based Instance Segmentation in Remote Sensing Images","venue":null,"work_id":"eff3f486-5a47-4e21-8e48-016f05d850c5","year":2024},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:3c90b6f4f5fbc2bfb5ecc8f6ddedb2d00a8b9abbb792a282876b84be101e2b85","observation_id":"771908f9-611b-4ac7-bbdd-263f39d020c0","resolution":{"observed_at":"2026-05-21T18:35:28.979825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"BiFA-YOLO: A Novel YOLO-Based Method for Arbitrary-Oriented Ship Detection in High-Resolution SAR Images","venue":null,"work_id":"3dfee141-d27a-4217-9029-f0bdb89a586a","year":2021},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:bd6ea9149f8367168ecb524614f4147ac944c8e43edccf5c7588b9a7ef9c9bc3","observation_id":"6c106103-6fe7-448f-89a5-0ddaf06e76dd","resolution":{"observed_at":"2026-05-21T18:35:28.971862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Contextual Region-Based Convolutional Neural Network with Multilayer Fusion for SAR Ship Detection","venue":null,"work_id":"c83c0fdf-b1fc-41df-b935-e57307a14702","year":2017},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:2ba5fd9afbe7512f06916b740a3c743fbfe15d76bf9d5fcc3921ece115c920e0","observation_id":"9b7cd6d4-2dc2-437b-9e2b-8f6acbda90d6","resolution":{"observed_at":"2026-05-21T18:35:28.966188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.00035","last_updated":"2023-04-28T18:18:07Z","snapshot_observed_at":"2026-08-16T15:36:53.667177Z","submitted_at":"2023-04-28T18:18:07Z","title":"SAM on Medical Images: A Comprehensive Study on Three Prompt Modes","version":1},"cited_work":{"arxiv_id":"2305.00035","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.00035","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sam on medical images: A comprehensive study on three prompt modes","venue":null,"work_id":"14aad36a-9b62-433f-a300-edfab04614d9","year":2023},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"cited_paper":"/paper/2305.00035","citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:f232918229f7299953d898f8edbe526e48c34bf03123605c1ca16f04f8310e5e","observation_id":"852da6fe-ff25-4316-bcec-362598332ea9","resolution":{"observed_at":"2026-05-10T05:56:11.060194Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"Segment anything in medical images","venue":null,"work_id":"9a0ed7dd-035a-439a-bc36-494301f84bd7","year":2024},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:fd92b9a3e64524369880ef79079d0eb016b895146c72b5e782184c6128e1d3f1","observation_id":"a7b85513-eb7b-49ec-8f22-1924a84b14df","resolution":{"observed_at":"2026-05-21T18:35:28.975667Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-06-05T21:23:00.469572Z","title":"HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmenta- tion","venue":null,"work_id":"fd6656ae-38a3-4073-9d57-a519c8bc1104","year":2020},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:6aed42fcb4ac31347b3a2951da47f3a00a7feafc35e65a6925a89befcf433e4a","observation_id":"4d061c73-df99-416e-8433-199e29c181f8","resolution":{"observed_at":"2026-05-21T18:35:28.982780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2507.9562","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges","venue":null,"work_id":"e6ede414-0ad9-4476-882d-876956ed4111","year":2025},"citing_paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T05:54:47.183674Z"},"links":{"citing_paper":"/paper/2604.17920"},"observation_digest":"sha256:35331176789783e39aa65fc0437dd062982a9d29637c4fc899419a4bc3010b7a","observation_id":"c4d10253-085b-41f1-bd0f-5613763a339a","resolution":{"observed_at":"2026-05-10T05:56:11.062722Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.17920","last_updated":"2026-04-20T07:57:11Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-04T05:20:10.005182Z","submitted_at":"2026-04-20T07:57:11Z","title":"Prompting Foundation Models for Zero-Shot Ship Instance Segmentation in SAR Imagery"},"reference_resolution":{"displayed":19,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":4,"verified_fuzzy":15},"total_outbound_references":19},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2604.17920."}