{"as_of":"2026-08-18T16:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9465c8c48206f0e5328490895740a171432d4926da2d2bb8f3b737b5bcd366c5","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T21:50:16.075787Z","state":"measured"},{"denominator":27,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":27,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T10:16:47.060463Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T21:41:15.755338Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03765","snapshot_observed_at":"2026-08-03T10:16:47.060463Z","title":"arXiv preprint arXiv:2501.03765, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.10912","last_updated":"2026-05-27T18:31:30Z","snapshot_observed_at":"2026-08-17T15:03:33.571905Z","submitted_at":"2026-01-16T00:06:39Z","title":"Graph Neural Network Reveals the Cortical Morphology of Local Brain Aging in Normal Cognition and Alzheimer's Disease","version":5},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T10:16:47.060463Z"},"links":{"cited_paper":"/paper/2501.03765","citing_paper":"/paper/2601.10912"},"observation_digest":"sha256:2d5266cd2596f6f68c6992e8fc16c50ac7134d293051754ad84c172569ba7a05","observation_id":"bb460bd4-f447-4e9f-ad09-05f2e141e85d","resolution":{"observed_at":"2026-08-03T10:16:47.060463Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"cited_work":{"arxiv_id":"2501.03765","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.03765","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"9489a231-8828-44a8-9b5f-a3c6b01bcc27","year":2020},"citing_paper":{"arxiv_id":"2604.24234","last_updated":"2026-08-14T03:48:43Z","snapshot_observed_at":"2026-08-18T16:09:25.780031Z","submitted_at":"2026-04-27T09:43:10Z","title":"Graph-augmented Segmentation of Complex Shapes in Laser Powder bed Fusion for Enhanced In Situ Inspection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T04:37:04.163205Z"},"links":{"cited_paper":"/paper/2501.03765","citing_paper":"/paper/2604.24234"},"observation_digest":"sha256:8cb5fef1003037e9a6ed43e54a0701a79992937db0f7f6c6138f4d3db542110a","observation_id":"1ca9eac1-3ae4-4875-9767-fb89c9c45a4e","resolution":{"observed_at":"2026-05-11T21:41:15.758648Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.03765/citation-record","integrity":"/paper/2501.03765/integrity","json":"/paper/2501.03765/citation-record.json","paper":"/paper/2501.03765"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:50:15.812873Z","title":null,"venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.812873Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:52f1f0ce817f3e06d1c2094951e83c8fa19c432f86b6e3a9f04a2f002fe84d4e","observation_id":"6def0f24-cb2c-4506-9b4e-e84fa0c7ba4b","resolution":{"observed_at":"2026-08-10T21:50:15.812873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1505.04597","last_updated":"2015-05-18T11:28:37Z","snapshot_observed_at":"2026-08-15T21:30:31.645090Z","submitted_at":"2015-05-18T11:28:37Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.04597","snapshot_observed_at":"2026-08-10T21:50:15.819499Z","title":"Ronneberger, P","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.819499Z"},"links":{"cited_paper":"/paper/1505.04597","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:e85ac580eee171da2f0b1a9ea2c44d138d7fced374b9c0c0bed2c10e9925f213","observation_id":"8e334d30-3e84-440d-a807-10fc89ea118d","resolution":{"observed_at":"2026-08-10T21:50:15.819499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.10165","last_updated":"2018-07-18T04:08:21Z","snapshot_observed_at":"2026-08-14T18:50:40.592878Z","submitted_at":"2018-07-18T04:08:21Z","title":"UNet++: A Nested U-Net Architecture for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.10165","snapshot_observed_at":"2026-08-10T21:50:15.833361Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.833361Z"},"links":{"cited_paper":"/paper/1807.10165","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:ab7a7b83a3e8c5563aaed369c2a25e6cbe74f0ae15b889e1054631ed49da7250","observation_id":"cb347f4c-b1ee-4c0c-a4d3-cef65ad742ad","resolution":{"observed_at":"2026-08-10T21:50:15.833361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.05537","last_updated":"2021-05-12T09:30:26Z","snapshot_observed_at":"2026-08-16T18:25:18.986045Z","submitted_at":"2021-05-12T09:30:26Z","title":"Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.05537","snapshot_observed_at":"2026-08-10T21:50:15.850186Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.850186Z"},"links":{"cited_paper":"/paper/2105.05537","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:1519b42a6ed90e249d1419c28d80293f6c01d46004fa6d78a40660698dee8618","observation_id":"2517264b-ef4e-422c-ae66-7702cd09b28c","resolution":{"observed_at":"2026-08-10T21:50:15.850186Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.13281","last_updated":"2023-01-05T13:24:13Z","snapshot_observed_at":"2026-08-16T16:57:30.476717Z","submitted_at":"2022-05-26T11:38:04Z","title":"Surround-view Fisheye Camera Perception for Automated Driving: Overview, Survey and Challenges","version":2},"cited_work":{"arxiv_id":"2205.13281","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.13281","snapshot_observed_at":"2026-08-10T21:50:17.227291Z","title":"Surround-view Fisheye Camera Perception for Automated Driving: Overview, Survey and Challenges","venue":"cs.CV","work_id":"e460aba2-c0f4-434a-b7ed-b0b7c1e18480","year":2022},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.863122Z"},"links":{"cited_paper":"/paper/2205.13281","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:b8bc511690483559ca2c1dab2429a8915d8fc0135a962cb51baa90a9e209c3a2","observation_id":"7d6a9eb6-6b4f-49e0-909e-76586a2608a0","resolution":{"observed_at":"2026-08-10T21:50:17.274743Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T21:50:15.875028Z","title":"C., Hagenbuchner, M., and Monfardini, G","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.875028Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:b1c48744e0bc83cb797b471ff9f0db3beb10a98eaf4a8c24410fb286c1f9a6cf","observation_id":"f962be38-541f-4b22-bd92-bf9d5d8d0ebf","resolution":{"observed_at":"2026-08-10T21:50:15.875028Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.00272","last_updated":"2022-11-04T14:45:03Z","snapshot_observed_at":"2026-08-16T16:56:06.640850Z","submitted_at":"2022-06-01T07:01:04Z","title":"Vision GNN: An Image is Worth Graph of Nodes","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.00272","snapshot_observed_at":"2026-08-10T21:50:15.882317Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.882317Z"},"links":{"cited_paper":"/paper/2206.00272","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:9d49421fe5e004838cb937962f3ffa6485b6d840370088f0c2d3200d903a2ad5","observation_id":"3dccf310-b654-44d1-8629-4d78742805ee","resolution":{"observed_at":"2026-08-10T21:50:15.882317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08187","last_updated":"2024-04-12T01:36:00Z","snapshot_observed_at":"2026-08-16T14:01:33.881382Z","submitted_at":"2024-04-12T01:36:00Z","title":"Adapting CNNs for Fisheye Cameras without Retraining","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.08187","snapshot_observed_at":"2026-08-10T21:50:15.887783Z","title":"Griffiths and D","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.887783Z"},"links":{"cited_paper":"/paper/2404.08187","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:9eb50e28cfc7b079f368706025f07cba84f06d3bcb094071d86893dfe295ae0f","observation_id":"d6ac206c-f861-4468-926b-2ae7cc991441","resolution":{"observed_at":"2026-08-10T21:50:15.887783Z","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":"2026-08-10T21:50:17.825410Z","title":null,"venue":null,"work_id":"667f24b8-3eb3-4e89-be9c-5afeb7dd295d","year":2010},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.894115Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:756dff842557f0eb4ee0d3aca19d8d1af2b6e81194da3b7fc6a562981605efcd","observation_id":"9e80b1ea-f19b-4d16-9460-54af3e1523b9","resolution":{"observed_at":"2026-08-10T21:50:17.859918Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.01489","last_updated":"2021-07-02T22:16:13Z","snapshot_observed_at":"2026-08-18T14:42:33.319955Z","submitted_at":"2019-05-04T13:14:12Z","title":"WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.01489","snapshot_observed_at":"2026-08-10T21:50:15.901023Z","title":"Yogamani, C","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.901023Z"},"links":{"cited_paper":"/paper/1905.01489","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:130a3ffd22747c8a49d3bd620867d7e16a3f0da7eaa403bd0923ddd693d9020f","observation_id":"943de4fa-ce62-493e-9646-2eed06d39635","resolution":{"observed_at":"2026-08-10T21:50:15.901023Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.01397","last_updated":"2016-05-04T19:49:17Z","snapshot_observed_at":"2026-08-15T23:25:55.061592Z","submitted_at":"2016-05-04T19:49:17Z","title":"Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.01397","snapshot_observed_at":"2026-08-10T21:50:15.907888Z","title":"Gutman, N","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.907888Z"},"links":{"cited_paper":"/paper/1605.01397","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:56cba5a9ee0e9033ded87e76f0d5d97183439d05c37b273ecef23b1bf81353cd","observation_id":"7f52cbff-4cbb-4e97-bb83-a3b9845321ef","resolution":{"observed_at":"2026-08-10T21:50:15.907888Z","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":"2026-08-10T21:50:17.738761Z","title":"Muhammad, T","venue":null,"work_id":"356b2c78-8804-403e-b951-4ce8f12047b0","year":null},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.916292Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:e35a45551f6df4e12a5005abe3ea24427a3133c5af61840801523a57c7e3833c","observation_id":"8d46212a-5404-41a8-9236-5a25723310a5","resolution":{"observed_at":"2026-08-10T21:50:17.766005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16647","last_updated":"2024-10-01T09:22:39Z","snapshot_observed_at":"2026-08-17T22:47:09.357983Z","submitted_at":"2024-07-23T17:02:24Z","title":"Deformable Convolution Based Road Scene Semantic Segmentation of Fisheye Images in Autonomous Driving","version":2},"cited_work":{"arxiv_id":"2407.16647","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.16647","snapshot_observed_at":"2026-08-10T21:50:16.667439Z","title":"Deformable Convolution Based Road Scene Semantic Segmentation of Fisheye Images in Autonomous Driving","venue":"cs.CV","work_id":"42eabc4c-44fc-4521-ae97-ec4789ba6391","year":2024},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.944745Z"},"links":{"cited_paper":"/paper/2407.16647","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:fd4a168771d21ef9c187f5c1b2f60558148dd0adca8d9042af2e6e7beed3f216","observation_id":"39674a06-96eb-4aaa-bcf6-62261bbe2094","resolution":{"observed_at":"2026-08-10T21:50:16.675395Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.14030","last_updated":"2021-08-17T16:41:34Z","snapshot_observed_at":"2026-08-13T19:24:14.214828Z","submitted_at":"2021-03-25T17:59:31Z","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.14030","snapshot_observed_at":"2026-08-10T21:50:15.961355Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.961355Z"},"links":{"cited_paper":"/paper/2103.14030","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:f82f0a273932449f93c762b36a84cfcec9f914c4d268eae879bd731e2b4f87e5","observation_id":"b57536c5-aaba-4d31-a9e1-e67652fd0279","resolution":{"observed_at":"2026-08-10T21:50:15.961355Z","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":"2026-08-16T09:25:53.087782Z","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":"2026-08-10T21:50:15.981752Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.981752Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:0eef683470df3a591fd2bcb6c4f22c3866ef784239f5ddad624be49e15a05ee8","observation_id":"cf854bc0-dd02-4131-8f45-e78c2476179b","resolution":{"observed_at":"2026-08-10T21:50:15.981752Z","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":"2026-08-10T21:50:17.604788Z","title":null,"venue":null,"work_id":"3924b2cd-b19f-4f2c-94db-ab99093ade00","year":2018},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.001122Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:2355a3c827277c5e3376d2e6de1b5e22ba201444fa4ebc333d25bb4a3047be42","observation_id":"08752432-d53a-44b3-a22d-dcb90692ad0a","resolution":{"observed_at":"2026-08-10T21:50:17.642812Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02658","last_updated":"2023-07-05T21:19:13Z","snapshot_observed_at":"2026-08-16T15:18:24.520150Z","submitted_at":"2023-07-05T21:19:13Z","title":"Spherical Feature Pyramid Networks For Semantic Segmentation","version":1},"cited_work":{"arxiv_id":"2307.02658","doi":null,"metadata_source":"pith","pith_arxiv_id":"2307.02658","snapshot_observed_at":"2026-08-10T21:50:16.588242Z","title":"Spherical Feature Pyramid Networks For Semantic Segmentation","venue":"cs.CV","work_id":"9b94ab10-2a6b-4409-8853-126742db0519","year":2023},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.018786Z"},"links":{"cited_paper":"/paper/2307.02658","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:068e60a2cf9c78f2952333c3bc43a63b6c148245d8b040b07edc3b3ab7547bd4","observation_id":"c6a6de5b-1670-4aa4-a4cd-32d6403ffb0f","resolution":{"observed_at":"2026-08-10T21:50:16.594613Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T21:50:16.025022Z","title":"Scaramuzza, A","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.025022Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:521bc65413add3db419e2f1afaab218f7efcf799cdeaf297a6a7250a03fe39f6","observation_id":"8ad2e8fd-9a9b-4379-9a14-768852814286","resolution":{"observed_at":"2026-08-10T21:50:16.025022Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-08-17T10:49:36.026134Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-10T21:50:16.033412Z","title":"N., and Welling, M","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.033412Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:3abcfd761ce512604f31d1d60aeca328e28dff0c63b100cde6acdd7cc38c76e3","observation_id":"f1f08c4d-9365-4f8e-8eba-29bdf92a74bd","resolution":{"observed_at":"2026-08-10T21:50:16.033412Z","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":"2026-08-10T21:50:16.044755Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.044755Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:41c788b74722802bbe071e805ad3019aba1879bee4628f4af2556cdb46743ab0","observation_id":"ca651530-7514-4f9f-be3c-452e370e5b60","resolution":{"observed_at":"2026-08-10T21:50:16.044755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03762","last_updated":"2023-08-02T00:41:18Z","snapshot_observed_at":"2026-08-17T01:19:18.409791Z","submitted_at":"2017-06-12T17:57:34Z","title":"Attention Is All You Need","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03762","snapshot_observed_at":"2026-08-10T21:50:16.054212Z","title":"Vaswani, N","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.054212Z"},"links":{"cited_paper":"/paper/1706.03762","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:278b1b3dd69e7f1c7ea6093428d9b2c08821149849d3295fcd00ff3b9c7fa1f1","observation_id":"cc8acd67-e50e-48ba-8325-6861a02a7518","resolution":{"observed_at":"2026-08-10T21:50:16.054212Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00199","last_updated":"2022-06-22T21:37:18Z","snapshot_observed_at":"2026-08-16T17:17:56.169434Z","submitted_at":"2022-03-01T03:08:47Z","title":"Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00199","snapshot_observed_at":"2026-08-10T21:50:16.060148Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.060148Z"},"links":{"cited_paper":"/paper/2203.00199","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:a7c3f2b412ae8c73afd5f3cda352af37452b34f0675abbb2805ea4b3539704d1","observation_id":"a7f3c58e-406c-452f-9c09-3da0342b9139","resolution":{"observed_at":"2026-08-10T21:50:16.060148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.11636","last_updated":"2020-06-20T19:12:51Z","snapshot_observed_at":"2026-07-06T09:31:02.537289Z","submitted_at":"2020-06-20T19:12:51Z","title":"Joint Demosaicking / Rectification of Fisheye Camera Images using Multi-color Graph Laplacian Regularization","version":1},"cited_work":{"arxiv_id":"2006.11636","doi":null,"metadata_source":"pith","pith_arxiv_id":"2006.11636","snapshot_observed_at":"2026-08-10T21:50:16.186561Z","title":"Joint Demosaicking / Rectification of Fisheye Camera Images using Multi-color Graph Laplacian Regularization","venue":"eess.IV","work_id":"182c0f17-821b-4f44-bd74-63f1c8a8d428","year":2020},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.067408Z"},"links":{"cited_paper":"/paper/2006.11636","citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:12e75c3491d2aad7bbdaa908e313c52dfdabf39323b55b3e3bcb002391e36aa7","observation_id":"dbd1fec2-dce4-4a3f-ab3e-a9f2ac923660","resolution":{"observed_at":"2026-08-10T21:50:16.196231Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T21:50:16.075787Z","title":"Fidon, W","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:16.075787Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:1155ceec0033caa5674c24d6fb2d5e3476e0716de6ed2b1636a362055faf4585","observation_id":"d49b1816-cbf7-4a85-8116-77b1be205d54","resolution":{"observed_at":"2026-08-10T21:50:16.075787Z","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":"2022.32076","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:50:16.773607Z","title":null,"venue":null,"work_id":"fa36d928-e71d-4249-9cd2-d62b7c8b1ad0","year":2022},"citing_paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-10T21:50:15.926924Z"},"links":{"citing_paper":"/paper/2501.03765"},"observation_digest":"sha256:06d509be12428472762651ada673d5b4cf669c0eae2a4e6992a67fed21ca79ed","observation_id":"3362b9ff-7ced-4cd7-8289-c7fd8bc1e864","resolution":{"observed_at":"2026-08-10T21:50:16.782785Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.03765","last_updated":"2025-01-19T11:34:58Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T01:11:37.751931Z","submitted_at":"2025-01-07T13:09:44Z","title":"Image Segmentation: Inducing graph-based learning"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":19,"verified_exact":4,"verified_fuzzy":1},"total_outbound_references":25},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 2 inbound Pith citation observations for arXiv:2501.03765."}