{"as_of":"2026-08-08T23:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6d3258a6f50534a95926d0c8788235d452c555a233b1b18a8c8c002e9325cf92","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:28:36.550194Z","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":"2026-07-02T02:26:26.455377Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-08-07T15:28:36.550194Z","title":"3d ux-net: A large kernel volumetric convnet modernizing hierarchical transformer for medical image seg- mentation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.17096","last_updated":"2025-08-27T16:47:29Z","snapshot_observed_at":"2026-08-08T00:16:53.003272Z","submitted_at":"2025-05-21T04:02:17Z","title":"TAGS: 3D Tumor-Adaptive Guidance for SAM","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:28:36.550194Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2505.17096"},"observation_digest":"sha256:1b957a106e8442e9189876193a176a319605fc65bf58b5e6ca15f6fa541efea2","observation_id":"a326f3f4-899b-4972-8dd7-2b538d1362fd","resolution":{"observed_at":"2026-08-07T15:28:36.550194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-08-07T10:26:55.892236Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.05297","last_updated":"2025-06-05T17:49:46Z","snapshot_observed_at":"2026-08-08T14:26:48.715708Z","submitted_at":"2025-06-05T17:49:46Z","title":"DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T10:26:55.892236Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2506.05297"},"observation_digest":"sha256:2ac382951a1e5bf5f703a6a3b267b63e514e5f797892230410db06a2d313800d","observation_id":"1b653efa-53cd-4511-810b-d808dc36fe52","resolution":{"observed_at":"2026-08-07T10:26:55.892236Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-08-06T19:10:56.886563Z","title":"arXiv preprint arXiv:2209.15076 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.07126","last_updated":"2025-07-08T18:56:01Z","snapshot_observed_at":"2026-08-08T22:54:42.603404Z","submitted_at":"2025-07-08T18:56:01Z","title":"DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:10:56.886563Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2507.07126"},"observation_digest":"sha256:39160e71f7790fede816441315107f19a8651ea61ca011456167dc202cb56dfc","observation_id":"52583f37-fb4f-4527-8c9d-fb0f458c2774","resolution":{"observed_at":"2026-08-06T19:10:56.886563Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":"2209.15076","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-07-02T02:26:26.455377Z","title":"arXiv preprint arXiv:2209.15076 , year=","venue":null,"work_id":"b18e7bad-201a-4df6-b52c-6175c2a3307f","year":2022},"citing_paper":{"arxiv_id":"2604.05515","last_updated":"2026-04-07T07:13:36Z","snapshot_observed_at":"2026-08-01T22:51:50.976529Z","submitted_at":"2026-04-07T07:13:36Z","title":"Geometrical Cross-Attention and Nonvoid Voxelization for Efficient 3D Medical Image Segmentation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T20:10:50.138588Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2604.05515"},"observation_digest":"sha256:f602394854c6a43a7afbed98073bcbb301c1e1821ee3c5e4d4a08c3551471796","observation_id":"2707d6f0-ec04-4cff-baff-a589f4299c20","resolution":{"observed_at":"2026-05-10T22:10:49.655201Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":"2209.15076","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-07-02T02:26:26.455377Z","title":"arXiv preprint arXiv:2209.15076 , year=","venue":null,"work_id":"b18e7bad-201a-4df6-b52c-6175c2a3307f","year":2022},"citing_paper":{"arxiv_id":"2605.07082","last_updated":"2026-05-08T01:02:36Z","snapshot_observed_at":"2026-07-06T23:19:30.387067Z","submitted_at":"2026-05-08T01:02:36Z","title":"ImplantMamba: Long-range Sequential Modeling Mamba For Dental Implant Position Prediction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-11T01:30:29.112699Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2605.07082"},"observation_digest":"sha256:54988650461972dbd0ef2bd9ac4f4c9ac3ff691947d430119f5f41f5faa3740c","observation_id":"630b2ecc-7c01-4738-aff0-9c5211ffaec4","resolution":{"observed_at":"2026-05-11T01:45:51.635830Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":"2209.15076","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-07-02T02:26:26.455377Z","title":"arXiv preprint arXiv:2209.15076 , year=","venue":null,"work_id":"b18e7bad-201a-4df6-b52c-6175c2a3307f","year":2022},"citing_paper":{"arxiv_id":"2605.11434","last_updated":"2026-05-12T02:32:58Z","snapshot_observed_at":"2026-07-06T23:23:16.461539Z","submitted_at":"2026-05-12T02:32:58Z","title":"FEFormer: Frequency-enhanced Vision Transformer for Generic Knowledge Extraction and Adaptive Feature Fusion in Volumetric Medical Image Segmentation","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-05-13T00:49:06.110219Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2605.11434"},"observation_digest":"sha256:410477a6711eac1d3af863bb36132001182146ec3e54a71a764c25c492c94698","observation_id":"0bba1918-d500-4586-9cd6-8ac334912485","resolution":{"observed_at":"2026-05-13T02:17:08.049681Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":"2209.15076","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-07-02T02:26:26.455377Z","title":"arXiv preprint arXiv:2209.15076 , year=","venue":null,"work_id":"b18e7bad-201a-4df6-b52c-6175c2a3307f","year":2022},"citing_paper":{"arxiv_id":"2606.03566","last_updated":"2026-06-02T12:32:43Z","snapshot_observed_at":"2026-07-06T23:43:50.943530Z","submitted_at":"2026-06-02T12:32:43Z","title":"Efficient Transformer-Based Localized Patch Sampling for Choroid Plexus Segmentation in Multiple Sclerosis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-28T10:57:39.138510Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2606.03566"},"observation_digest":"sha256:ed93d937f06c91d2f9452236fcb0ad1c52d8a9f6463895b777ef65dcd12f5a34","observation_id":"89a37b7b-1407-4e4c-bce3-27439b80182f","resolution":{"observed_at":"2026-07-02T02:26:26.458280Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-07-11T16:38:56.238848Z","title":"arXiv preprint arXiv:2209.15076 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04599","last_updated":"2026-07-06T02:01:59Z","snapshot_observed_at":"2026-08-06T04:54:53.317593Z","submitted_at":"2026-07-06T02:01:59Z","title":"Displacement Preserving Relational Distillation for Robust Medical Segmentation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-11T16:38:56.238848Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2607.04599"},"observation_digest":"sha256:a50e90f1ebf5e530a790cfd38c603ab913dec8a2307fc9b923209eb1f6dfed88","observation_id":"39f1f168-cf6e-4b89-9c77-a82d65731c80","resolution":{"observed_at":"2026-07-11T16:38:56.238848Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15076","last_updated":"2023-03-02T03:58:57Z","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15076","snapshot_observed_at":"2026-08-03T14:59:59.737219Z","title":"arXiv preprint arXiv:2209.15076 (2022) SAM+D 17","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29033","last_updated":"2026-07-31T05:11:25Z","snapshot_observed_at":"2026-08-08T22:39:37.898972Z","submitted_at":"2026-07-31T05:11:25Z","title":"SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T14:59:59.737219Z"},"links":{"cited_paper":"/paper/2209.15076","citing_paper":"/paper/2607.29033"},"observation_digest":"sha256:c59c989e5d38255deb3af7bdbd57fe7e707e334dc049238e73c6f288fac49c97","observation_id":"83197892-ef7e-4e4f-ad48-185fb57450e4","resolution":{"observed_at":"2026-08-03T14:59:59.737219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2209.15076/citation-record","integrity":"/paper/2209.15076/integrity","json":"/paper/2209.15076/citation-record.json","paper":"/paper/2209.15076"},"outbound":[],"paper":{"arxiv_id":"2209.15076","last_updated":"2023-03-02T03:58:57Z","latest_version":4,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T13:57:58.305779Z","submitted_at":"2022-09-29T19:54:13Z","title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2209.15076."}