{"as_of":"2026-08-08T09:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1326c151476b81ebe5aa9c15f4b43c64261acec79806e9b6d5b0a523c2bddcec","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:36:29.790104Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2505.24167/citation-record","integrity":"/paper/2505.24167/integrity","json":"/paper/2505.24167/citation-record.json","paper":"/paper/2505.24167"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:32.220737Z","title":"A fast diffeomorphic image registration algorithm","venue":null,"work_id":"f8d9b78c-be03-4eaa-8229-471e3a568420","year":2007},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:28.489584Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:deb649c362a065f3d5463a4e8b9f216b96fca239edd5a61da6a7275bc873c160","observation_id":"b161e184-5dbd-4046-8af2-39afcc7d3189","resolution":{"observed_at":"2026-08-07T12:36:32.298054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:31.975535Z","title":"Four-dimensional deformable image registration using trajectory modeling","venue":null,"work_id":"f554acf4-3158-466c-852f-1e24c6ba6279","year":2009},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:28.579808Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:03aaa1ce65ea524b878129edd36eabbc634df61230548b7ca3d8eb9f06802727","observation_id":"20a8bdb1-18fa-45d9-bb68-5fb08a314594","resolution":{"observed_at":"2026-08-07T12:36:32.081292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:31.773320Z","title":"A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets","venue":null,"work_id":"69ddbc83-6d8b-4aed-9853-6c5c0de90d29","year":2009},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:28.676561Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:0483a8910cca004315e1a6603f02166f92fabbcf888b8d342ae0e1ab03510d82","observation_id":"8c16154b-0706-4897-983d-c40980835a9e","resolution":{"observed_at":"2026-08-07T12:36:31.866966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:31.577333Z","title":"Unsupervised learning of diffeomorphic image registration via transmorph","venue":null,"work_id":"69d81d5c-83a9-49da-a32c-5aab886aea3d","year":2022},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:28.777035Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:9cebd8c0ea50105116e0fd044a198c42aea6f8b026b7568531cb7c54d1c1f91e","observation_id":"ab2204f7-535e-45b4-bda1-9d1ed249bd90","resolution":{"observed_at":"2026-08-07T12:36:31.688603Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:31.358301Z","title":"Transmorph: Transformer for unsupervised medical image registration","venue":null,"work_id":"ba5b151e-d41b-4691-8037-ddbf7f3cfb66","year":2022},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:28.854149Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:cb3f16c99e96b88a9a1a4e6e5888b75e96534178112c79feb9726e645db76e3b","observation_id":"2dd09196-256b-4f48-a911-101cb5ccdeb5","resolution":{"observed_at":"2026-08-07T12:36:31.471643Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:31.190147Z","title":"A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond","venue":null,"work_id":"e89547c2-dcf4-4065-8d47-0e9083eb6b1d","year":2024},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:28.942030Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:98ccb83e65fbeff52dc25b6091f1f2280b50459c142968552fe68d60343a177e","observation_id":"18297568-d8d1-4ea2-b04b-f461b2fdaf2a","resolution":{"observed_at":"2026-08-07T12:36:31.258634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:31.001866Z","title":"Freesurfer","venue":null,"work_id":"4461b3ae-5100-4ab7-b495-37bcee28dd90","year":2012},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.039216Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:28d0f4746422f516469ed14545339c98cc439614e8db54286a56b38a690e3b4a","observation_id":"89c70a77-5d5b-4901-b8f1-03b95aac5a48","resolution":{"observed_at":"2026-08-07T12:36:31.091819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T12:36:29.119914Z","title":"Masked autoencoders are scalable vision learners","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.119914Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:c0674bf0d6e42b65a4e67e8ea47bc6afbbfd48c9c3c1b11c9ac31fe1f5aa097c","observation_id":"06f1ff7f-f3f3-42e3-9dea-3ee8dd0af6b4","resolution":{"observed_at":"2026-08-07T12:36:29.119914Z","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":"2026-08-07T12:36:30.834972Z","title":"Mrf-based deformable registration and ventilation estimation of lung ct","venue":null,"work_id":"0b3de326-86cd-4630-877b-2d966ef0ee78","year":2013},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.207504Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:9e0fed21155588b2b22e703ccc34fe1de4ae08de7c1ecf3df0233c392af858db","observation_id":"fc7f73e6-c29a-40d4-ac5d-a7a9bba9aa2d","resolution":{"observed_at":"2026-08-07T12:36:30.891020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:30.673207Z","title":"Synthmorph: learning contrast-invariant registration without acquired images","venue":null,"work_id":"883a3e03-0bd7-4f57-9ffc-c5ef4c2cc7a2","year":2021},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.282012Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:5f1514f9fdeb8069cb58eea9f7e8b3edc2d508d9d7bb089c670debf801b324ef","observation_id":"3bd6e1a5-e40b-45e6-973d-1e9676ca60d7","resolution":{"observed_at":"2026-08-07T12:36:30.742056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T12:36:29.347524Z","title":"Segment anything","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.347524Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:ff4ed8fcd43349e9b8abc165cfc6be04564119360bc66574fd97becfd2444bc4","observation_id":"e4b68b3e-2d4a-4b56-a04a-ae84c6ec94eb","resolution":{"observed_at":"2026-08-07T12:36:29.347524Z","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":"2026-08-07T12:36:30.489268Z","title":"On finite difference jacobian computation in deformable image registration","venue":null,"work_id":"acfbcb24-4520-48a6-8bbb-2dd76f18fe14","year":2024},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.402612Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:1b6b2b7a4c95e8d4069103e398881e67cdb5dd6e726e9595614c95aafeeda839","observation_id":"6f38c444-e9cb-43af-b62b-ea8f18f616d0","resolution":{"observed_at":"2026-08-07T12:36:30.587742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:30.306612Z","title":"The nimh intramural healthy volunteer dataset: A comprehensive meg, mri, and behavioral resource","venue":null,"work_id":"b186ef9c-650f-46ae-921d-c224da09582f","year":2022},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.496112Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:46b34219d1206a7a821597cac19133484424e1f4d717bcf51d7b1f6e304acafc","observation_id":"b1fd6f49-df51-4de6-bed8-7f36a6365958","resolution":{"observed_at":"2026-08-07T12:36:30.402713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-07T12:36:29.572858Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.572858Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:45ed55ae8789172682947316ac18b1959a559fee2ca4429cfaddfc42cff8924d","observation_id":"009141c6-7ba6-472a-9a71-c660a9b8908e","resolution":{"observed_at":"2026-08-07T12:36:29.572858Z","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":"2026-08-07T12:36:30.124734Z","title":"Improving noise","venue":null,"work_id":"23fc2faa-e100-40c4-9edd-f7de4015c581","year":2002},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.656366Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:bdbf8a5d77159652b6ae9586c11179631acd0e1eb655cb219ac79f42d1cdf639","observation_id":"faa660b1-d2f0-4b4b-b0ee-5642a11c812d","resolution":{"observed_at":"2026-08-07T12:36:30.199752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:36:29.921204Z","title":"Convexadam: Self-configuring dual-optimisation-based 3d multitask medical image registration","venue":null,"work_id":"5934eba3-04a7-4903-aa81-600ea7b6674a","year":2024},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.725740Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:39559b90561c7bd27aaa3f6537d890351bdddfd318da8251d876a7fd72b7f4a2","observation_id":"7470ca4e-d4a7-47ef-9f24-68daf2b2ae44","resolution":{"observed_at":"2026-08-07T12:36:30.044527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T12:36:29.790104Z","title":"Self-distillation: Towards efficient and compact neural networks","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T12:36:29.790104Z"},"links":{"citing_paper":"/paper/2505.24167"},"observation_digest":"sha256:782141656853c30d775f2c2090a83f0a6ffb3608eae5811f112544ae6e0fb8a8","observation_id":"d12dbf0f-e5bf-4add-ba33-3620bd826b9d","resolution":{"observed_at":"2026-08-07T12:36:29.790104Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.24167","last_updated":"2025-05-30T03:22:10Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T12:29:28.895986Z","submitted_at":"2025-05-30T03:22:10Z","title":"Pretraining Deformable Image Registration Networks with Random Images"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":13},"total_outbound_references":17},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2505.24167."}