{"as_of":"2026-08-09T10:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9c2868a5b772c132593ce0e9a198cd8d2f85d112afda3ec70b9cf15f57a37df0","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T04:29:05.752620Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2607.29568/citation-record","integrity":"/paper/2607.29568/integrity","json":"/paper/2607.29568/citation-record.json","paper":"/paper/2607.29568"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:29:00.776619Z","title":"Magnetic resonance imaging , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:00.776619Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:c35a935d07d54a8559243be81a4cd2465e89f88a83ab6eb4a415df8f9d37e6ae","observation_id":"fec061a9-dc9f-40a5-a5ce-c39fd920af18","resolution":{"observed_at":"2026-08-03T04:29:00.776619Z","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":"2026-08-03T04:29:00.923719Z","title":"Nature medicine , volume=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:00.923719Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:b972eb0baa4717ca3694320b19a1aadf1995fb60f7060ba8c3642ab6e4364353","observation_id":"2828d09c-69e2-469f-954c-05e3a1ba1b92","resolution":{"observed_at":"2026-08-03T04:29:00.923719Z","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":"2026-08-03T04:29:01.038906Z","title":"International Conference on Medical image computing and computer-assisted intervention , pages=","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.038906Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:18f70d02534ab82376389c5739bb8374d9596bb8580d04dfe13882b3de29d8b6","observation_id":"f2a83802-c52e-48d8-98dc-b3b963bad0e1","resolution":{"observed_at":"2026-08-03T04:29:01.038906Z","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":"2026-08-03T04:29:01.154224Z","title":"2016 fourth international conference on 3D vision (3DV) , pages=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.154224Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:7208ce03e8046f51d0254eb33df900a69446c11a1b5dadd8e7cb8c2b1653efff","observation_id":"c035d678-a073-402d-950f-8dba4cd23cfa","resolution":{"observed_at":"2026-08-03T04:29:01.154224Z","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":"2026-08-03T04:29:01.264512Z","title":"Journal of hepatology , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.264512Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:5cc564032a74e955b09f89aafd86fa1f75f897b0ec16a66f16d2cd419015b8ee","observation_id":"9da8f9c8-9dcf-4c48-86d9-e71d0c8d0457","resolution":{"observed_at":"2026-08-03T04:29:01.264512Z","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":"2026-08-03T04:29:01.407748Z","title":"Radiology , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.407748Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:acc388731baf193bb20b97ddb48e45294b7ebba6e85334f55af141ecd8de2d69","observation_id":"8930f1a7-b7a0-4966-801e-0b995808d124","resolution":{"observed_at":"2026-08-03T04:29:01.407748Z","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":"2026-08-03T04:29:01.561259Z","title":"Cancer Imaging , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.561259Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:1be512159417087ba976daca9c7147a729c3bcd83961ae29a480d6ea3712d589","observation_id":"4538c959-22bd-4e2b-9c88-7c42eb933c89","resolution":{"observed_at":"2026-08-03T04:29:01.561259Z","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":"2026-08-03T04:29:01.704052Z","title":"Best Practice & Research Clinical Gastroenterology , volume=","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.704052Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:903737f898678543b79a53d73fc658236521fd2384dd11691198aace3c8d576c","observation_id":"7ad4d92a-e7a0-4f2b-9127-19cfc9ccd54c","resolution":{"observed_at":"2026-08-03T04:29:01.704052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.10486","last_updated":"2018-09-27T12:25:52Z","snapshot_observed_at":"2026-07-06T07:04:39.537654Z","submitted_at":"2018-09-27T12:25:52Z","title":"nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.10486","snapshot_observed_at":"2026-08-03T04:29:01.805342Z","title":"arXiv preprint arXiv:1809.10486 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.805342Z"},"links":{"cited_paper":"/paper/1809.10486","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:39c17a678581eaaf06689e2aae228265516e5e28cda5a7a2b24dec37bf533fef","observation_id":"07f5d5f3-7be3-4363-82b2-aa83f6db86b2","resolution":{"observed_at":"2026-08-03T04:29:01.805342Z","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":"2026-08-03T04:29:01.896777Z","title":"Array , volume=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.896777Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:1387a67016154ca46567825a8e61458d4f5091e1420a73a4bc82471878ac3ce4","observation_id":"5c6f961c-84cb-40cb-8aa2-e8ae42bd005c","resolution":{"observed_at":"2026-08-03T04:29:01.896777Z","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":"2026-07-06T02:11:23.670680Z","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":"2026-08-03T04:29:01.969144Z","title":"arXiv preprint arXiv:2010.11929 , year=","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:01.969144Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:17b2d8334ea73c451c6556ba51f930da46ca8825e032cc2687c4455e593f56a7","observation_id":"5ae39b50-5c3c-432d-bd8c-bee203ea17d7","resolution":{"observed_at":"2026-08-03T04:29:01.969144Z","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":"2026-08-03T04:29:02.043415Z","title":"Proceedings of the IEEE/CVF winter conference on applications of computer vision , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.043415Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:aae99855cf27411a13170b603b97fe9fc03cb575353aab7696a2647107725924","observation_id":"f8e385b8-80ac-4237-b3e7-aee99fe7ab21","resolution":{"observed_at":"2026-08-03T04:29:02.043415Z","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":"2026-08-03T04:29:02.144814Z","title":"European conference on computer vision , pages=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.144814Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:0e6a6eb66162fae2b42cfb58f1efcaa763987d63075685c368cd91aa5fe05312","observation_id":"93350a4b-e514-4c34-a675-ef316686ae6d","resolution":{"observed_at":"2026-08-03T04:29:02.144814Z","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":"2026-08-03T04:29:02.276812Z","title":"IEEE Journal of Biomedical and Health Informatics , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.276812Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:09f8ca7cd7bbf9e4fc8ff0a3659b5cb65abb3d8b526471ab6d17290f18641e6f","observation_id":"fdadce94-9bdb-4d93-b27c-95926ffdfb73","resolution":{"observed_at":"2026-08-03T04:29:02.276812Z","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":"2026-08-03T04:29:02.439577Z","title":"The British journal of radiology , volume=","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.439577Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:fd76fad9a7c4d34a7264efa282bec27c86f6d662ea62c811584c2751adabf852","observation_id":"60d43a42-1956-4c91-add7-41e6ca7ba23c","resolution":{"observed_at":"2026-08-03T04:29:02.439577Z","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":"2026-08-03T04:29:02.598927Z","title":"Abdominal Radiology , volume=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.598927Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:1bce41498fb3997a9e1986aa2c668bf44e5562e5728afaa28a7325f09407d4e9","observation_id":"fcc4957d-d822-46df-89c3-9e6d82c56a48","resolution":{"observed_at":"2026-08-03T04:29:02.598927Z","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":"2026-08-03T04:29:02.721664Z","title":"CA: a cancer journal for clinicians , volume=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.721664Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:cc27a6216fe2bd3ce3ffb86e67bd1210747a322aba9fee2622dbc9852130d3a8","observation_id":"b1426eab-d3d7-44f4-9368-76064c223db7","resolution":{"observed_at":"2026-08-03T04:29:02.721664Z","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":"2026-08-03T04:29:02.845407Z","title":"Hepatology , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.845407Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:4096517f7af879327f759e0551f31947d32b200dee913313638fd04513d93cf1","observation_id":"d1b1a4e2-3305-4e66-a0aa-ad9ef1178d77","resolution":{"observed_at":"2026-08-03T04:29:02.845407Z","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":"2026-08-03T04:29:02.980760Z","title":"Hepatology , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:02.980760Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:82a9bedaccf1c5d51e2eb251ff31787aa9fc65d4f6f8b5e98a3da9ff2c8da44f","observation_id":"0906bb84-6fb5-4402-9792-afcf6f424a43","resolution":{"observed_at":"2026-08-03T04:29:02.980760Z","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":"2026-08-03T04:29:03.112747Z","title":"Hepatology , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.112747Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:7dbb4afe6ae562172f373feb489cdb966e3ba1051cbdedc370a09d6fd2a1765a","observation_id":"aa50ff5b-5b05-482c-a9a3-5d1420d1cff6","resolution":{"observed_at":"2026-08-03T04:29:03.112747Z","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":"2026-08-03T04:29:03.246428Z","title":"Machine Vision and Applications , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.246428Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:129eb617710e524f2b484387422f8087d35fdefbdf7a73190036c647b4fbfc02","observation_id":"ab0e4b7b-a079-49c7-9b55-08f1c2b21ada","resolution":{"observed_at":"2026-08-03T04:29:03.246428Z","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":"2026-08-03T04:29:03.376134Z","title":"Proceedings of the IEEE/CVF international conference on computer vision , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.376134Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:40944fab74b0881eb4d33b31bdbe04c0aba0a861f51d338c666884c4390a8c54","observation_id":"24b8524b-d8c9-491a-9e89-daae0d74fad9","resolution":{"observed_at":"2026-08-03T04:29:03.376134Z","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":"2026-08-03T04:29:03.475640Z","title":"arXiv preprint arXiv:2509.02379 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.475640Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:2289f99d8324b1ef538f5eea32078fc9f0bbf53f4150fa6d8063c19b448dd163","observation_id":"402567ad-b384-4315-b703-34a2ff7be25d","resolution":{"observed_at":"2026-08-03T04:29:03.475640Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.20909","last_updated":"2026-05-08T06:39:51Z","snapshot_observed_at":"2026-08-04T15:16:30.376993Z","submitted_at":"2025-08-28T15:38:50Z","title":"Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20909","snapshot_observed_at":"2026-08-03T04:29:03.592760Z","title":"arXiv preprint arXiv:2508.20909 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.592760Z"},"links":{"cited_paper":"/paper/2508.20909","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:b881e0968eb2be69d619d5b1c03de699a60f8878bb9c5d8876ccbabee4e77772","observation_id":"4ebf1ec2-df3a-45fe-b795-9facf275100b","resolution":{"observed_at":"2026-08-03T04:29:03.592760Z","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":"2026-08-03T04:29:03.638253Z","title":"arXiv preprint arXiv:1804.03999 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.638253Z"},"links":{"cited_paper":"/paper/1804.03999","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:c2079c78c969c38af87368def11156a1ec7d0a46d58e3a10eca5698d78d5d9c3","observation_id":"2c3fc9c1-13ad-497c-89f6-d8fb0c947c55","resolution":{"observed_at":"2026-08-03T04:29:03.638253Z","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":"2026-08-03T04:29:03.699427Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.699427Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:24f4cc4e4d7b202623a653993c3795a1bc50eb0ad5595e30213d8d806c3dfe2d","observation_id":"8ac83655-f7d8-49a3-8cc2-88b29fb3de76","resolution":{"observed_at":"2026-08-03T04:29:03.699427Z","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":"2026-08-03T04:29:03.751227Z","title":"ACM Computing Surveys , volume=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.751227Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:15ffb764906bfbbcdba4ca025d728719f87272e861bf47a0fc50bed52a6f7d97","observation_id":"dc1129a7-065d-4512-9503-1775b892023a","resolution":{"observed_at":"2026-08-03T04:29:03.751227Z","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":"2026-08-03T04:29:03.807265Z","title":"Scientific reports , volume=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.807265Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:8e02169df15e6177496aeddf115d453bcb5a651339055c0480dc89532a64a825","observation_id":"e3105c46-ca3c-4973-b4c5-742a2cd92e48","resolution":{"observed_at":"2026-08-03T04:29:03.807265Z","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":"2026-08-03T04:29:03.885309Z","title":"Magnetic Resonance Imaging Clinics , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.885309Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:72304b3f64382aa76c066ef87375d8e9059d86386574dbed95593b98516cbcbc","observation_id":"cd6e09e8-2b02-450e-95ab-b0345e0904ce","resolution":{"observed_at":"2026-08-03T04:29:03.885309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-06T05:58:29.182448Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-03T04:29:03.956314Z","title":"arXiv preprint arXiv:2304.07193 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:03.956314Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:39f125b5cd9b6a2b44d03a3cc6fe0103ee7d1fcfc9d11d7b7b97bde6594d15f4","observation_id":"34011ffd-8323-4267-9b7e-941a1fb9bfdc","resolution":{"observed_at":"2026-08-03T04:29:03.956314Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.10104","last_updated":"2025-08-13T18:00:55Z","snapshot_observed_at":"2026-07-06T22:12:35.584339Z","submitted_at":"2025-08-13T18:00:55Z","title":"DINOv3","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.10104","snapshot_observed_at":"2026-08-03T04:29:04.063694Z","title":"arXiv preprint arXiv:2508.10104 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.063694Z"},"links":{"cited_paper":"/paper/2508.10104","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:81672a7a4c427e2ca5c8d54541be719e4b5dfcbf68fc3d24863babec8c75e2f8","observation_id":"8caa9a0c-9d86-43d0-a403-822d84c68553","resolution":{"observed_at":"2026-08-03T04:29:04.063694Z","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":"2026-08-03T04:29:04.135572Z","title":"Medical Image Analysis , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.135572Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:277d9d355e3bc798e87f68622eeaa464c281e7b9979e9ab16f60396892fc93e3","observation_id":"a12d0bc2-df29-4ce0-8a91-6f4849acefbf","resolution":{"observed_at":"2026-08-03T04:29:04.135572Z","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":"2026-08-03T04:29:04.218439Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.218439Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:c36147e4bedb39d77211af48043150f522b52c07ccba4658b2c0294b94e1c2b0","observation_id":"a1cd6591-0e44-43cb-ab19-b8dd6b5448cc","resolution":{"observed_at":"2026-08-03T04:29:04.218439Z","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":"2026-08-03T04:29:04.298612Z","title":"Image and vision computing , volume=","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.298612Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:7c5bfad8eacc2f5a6444fe3b1834daf2fbc0d64e4d400aa8b487aa67fcde8c31","observation_id":"48840cf8-3cc6-4872-b7fa-96069d94f214","resolution":{"observed_at":"2026-08-03T04:29:04.298612Z","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":"2026-08-03T04:29:04.353422Z","title":"IEEE transactions on medical imaging , volume=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.353422Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:0746bd54e7f04f29d42631148ace27dd3d790c1d934529e19dfa0957b7108755","observation_id":"7b98b80e-8872-4da1-9e2d-53288c40de0c","resolution":{"observed_at":"2026-08-03T04:29:04.353422Z","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":"2026-08-03T04:29:04.419269Z","title":"International conference on medical image computing and computer-assisted intervention , pages=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.419269Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:f3d29a669c5776bda619c9179bf4aab7aca39a56e0baf9f968a99c3bdf885a4b","observation_id":"2fce5d83-d43f-4af9-b8e8-21267891310a","resolution":{"observed_at":"2026-08-03T04:29:04.419269Z","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":"2026-08-03T04:29:04.501744Z","title":"International conference on medical image computing and computer-assisted intervention , pages=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.501744Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:56324a77e34464e2e10e0e51f42f2ad4750eb101ddb980fc6975a3c3c0f7064f","observation_id":"7ed286c7-6d89-44c7-ab62-3d65001c0a56","resolution":{"observed_at":"2026-08-03T04:29:04.501744Z","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":"2026-08-03T04:29:04.548672Z","title":"Computer Methods and Programs in Biomedicine , volume=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.548672Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:aad4dedf71819b68a734e59320b22141cbef68cd7b984e01a8b726595548644a","observation_id":"678cdfd8-192a-4f01-9f3f-03433a172ded","resolution":{"observed_at":"2026-08-03T04:29:04.548672Z","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":"2026-08-03T04:29:04.621377Z","title":"IEEE transactions on medical imaging , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.621377Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:95adb47b232aa39b16b21f5bd29b2b78bc74069c09ff42b5b77cee280266606b","observation_id":"9668cac3-ed88-4d01-a5e8-20bbf0ac7fc3","resolution":{"observed_at":"2026-08-03T04:29:04.621377Z","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":"2026-08-03T04:29:04.704776Z","title":"International conference on medical image computing and computer-assisted intervention , pages=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.704776Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:7fbe54302c8558760534a7d95098552b9e6cc02263b03c215ddc470febc2006e","observation_id":"7c3584ae-1585-46b4-bb78-356018c01a17","resolution":{"observed_at":"2026-08-03T04:29:04.704776Z","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":"2026-08-03T04:29:04.761272Z","title":"Proceedings of the IEEE conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.761272Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:0c387790ec5eb529d6d1a34d21d2cdd3123ae221b61bf2a161e47300897f5e76","observation_id":"830f7007-498f-4fbc-bddf-772bcd4dad70","resolution":{"observed_at":"2026-08-03T04:29:04.761272Z","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":"2026-08-03T04:29:04.843353Z","title":"Proceedings of the IEEE/CVF international conference on computer vision , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.843353Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:17c2519f1db6f305366ec065c57f1be087f2c3f92d6b4d915cea5e6ebc9644c8","observation_id":"74a441c9-3d5d-45bb-a0a5-1bca23974db3","resolution":{"observed_at":"2026-08-03T04:29:04.843353Z","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":"2026-08-03T04:29:04.913434Z","title":"IEEE Transactions on Geoscience and Remote Sensing , volume=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.913434Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:d6b9b4caae99259827d2715606b0ba3e407b4afb4230e98d8c697456451be198","observation_id":"3ceb806e-198e-4334-9c63-8ca1375679a8","resolution":{"observed_at":"2026-08-03T04:29:04.913434Z","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":"2026-08-03T04:29:04.954667Z","title":"Proceedings of the AAAI conference on artificial intelligence , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:04.954667Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:2aeed1a3259f5ca957784df870f0ed5c55eab0a8c38ad4b3774340c4d93ba43f","observation_id":"f591dbfa-b408-45b1-9522-2c99d4c01c7b","resolution":{"observed_at":"2026-08-03T04:29:04.954667Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.08691","last_updated":"2023-07-17T17:50:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-17T17:50:36Z","title":"FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.08691","snapshot_observed_at":"2026-08-03T04:29:05.026143Z","title":"arXiv preprint arXiv:2307.08691 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.026143Z"},"links":{"cited_paper":"/paper/2307.08691","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:4d326c12bc5339eff672e8aeac7cb39fb36608cecd9d1b37b683b4fe97572783","observation_id":"c6ff0887-b62a-463a-a4cd-b38810136768","resolution":{"observed_at":"2026-08-03T04:29:05.026143Z","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":"2026-08-03T04:29:05.131425Z","title":"Medical image analysis , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.131425Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:5628ec3ba3fac27a0a6c715dff87a68ca91c1a2f8f127278ec8040427ed3a80b","observation_id":"fcf8edae-7f06-4671-ae8a-10f88f26efa6","resolution":{"observed_at":"2026-08-03T04:29:05.131425Z","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":"10.57760/sciencedb.12173","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"2024 , month=","venue":"ScienceDB","work_id":"6af04421-db6a-4fd9-b823-9e7ffe974d6b","year":2024},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.190722Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:c285c8f9c21abda7da2ffc6612ca65b00156690bb02ffacbc52416523533511a","observation_id":"8c699eb8-4f45-422b-acc5-190d57fa634f","resolution":{"observed_at":"2026-08-03T04:34:10.975819Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-03T04:29:05.270525Z","title":"Radiology: Artificial Intelligence , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.270525Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:3024a09aa67a07c4591b4f3f7129ee023af68051e05340562ca864e99e6e74b4","observation_id":"382665b2-d1a6-471d-9153-694ff8ef0dd4","resolution":{"observed_at":"2026-08-03T04:29:05.270525Z","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":"2026-08-03T04:29:05.322194Z","title":"Vision interface , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.322194Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:33f59c452ddc47655f12292b5e813daa989d268c8d6b4bdc7708e40e8b97b2e0","observation_id":"7049f98f-e6a7-47f3-a758-4f5db28fdd62","resolution":{"observed_at":"2026-08-03T04:29:05.322194Z","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":"2026-08-03T04:29:05.407635Z","title":"Optics letters , volume=","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.407635Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:a9c0b43fb2d74052f09bae8b2f65186d2efd2b60192ca388e89ac7bde0705d91","observation_id":"baae3112-18bd-43a4-b85f-613f02a8d657","resolution":{"observed_at":"2026-08-03T04:29:05.407635Z","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":"2026-08-03T04:29:05.460189Z","title":"Proceedings of the IEEE conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.460189Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:c9b33612a4c5589d3ae04898028b8abdb13231d0b04bdcf7052879eb69d83b9f","observation_id":"a8006dcb-636f-4e33-8030-f20296284fd7","resolution":{"observed_at":"2026-08-03T04:29:05.460189Z","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":"2026-08-03T04:29:05.537769Z","title":"BMC medical imaging , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.537769Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:efae0fa3a6d1daa54a23b2c40ae5caa2eaac88cc6bc910b78d6b60d48399239c","observation_id":"99ba161a-a10e-4cf1-8576-6519a5020b87","resolution":{"observed_at":"2026-08-03T04:29:05.537769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-03T04:29:05.619758Z","title":"arXiv preprint arXiv:1711.05101 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.619758Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:86b3d6841da9498e72691d65ea6078be89d6080157c89e335b7998c7baa50244","observation_id":"88f31dc4-d824-4e76-ae09-10c2d0136f05","resolution":{"observed_at":"2026-08-03T04:29:05.619758Z","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":"2026-08-03T04:29:05.677228Z","title":"International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.677228Z"},"links":{"citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:47fdaccd01d7f5dbc3d2178e7796fb56d09c87c46dcdd1087cb81843303e593d","observation_id":"db7f5246-f88d-42a7-82a3-d507ea76a16b","resolution":{"observed_at":"2026-08-03T04:29:05.677228Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.04430","last_updated":"2021-01-13T17:43:14Z","snapshot_observed_at":"2026-08-07T17:36:34.529110Z","submitted_at":"2018-09-12T13:42:38Z","title":"Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.04430","snapshot_observed_at":"2026-08-03T04:29:05.752620Z","title":"arXiv preprint arXiv:1809.04430 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-03T04:29:05.752620Z"},"links":{"cited_paper":"/paper/1809.04430","citing_paper":"/paper/2607.29568"},"observation_digest":"sha256:79b8236b9f9d677daae3015878f30f857bd373444a6117c297bc27ef5f5ddb3d","observation_id":"e4396347-4132-4366-9a51-22c3edc98b2d","resolution":{"observed_at":"2026-08-03T04:29:05.752620Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.29568","last_updated":"2026-07-31T15:55:54Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T19:58:04.678253Z","submitted_at":"2026-07-31T15:55:54Z","title":"DynoDINO: Harnessing Dynamic Latent Information from DINO Features for Multi-Phase Medical Image Segmentation"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":54,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":55},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2607.29568."}