{"as_of":"2026-08-19T23:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:45b1a5ba773f8d9eb9bfb25f36d0f1a20618aae3ef68a7c4c441770a7da43a45","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:57:20.935951Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-20T10:13:11.857540Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-08-10T20:57:20.935951Z","title":"Self-explainable ai for medical image analysis: A survey and new outlooks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07021","last_updated":"2025-01-20T04:00:48Z","snapshot_observed_at":"2026-08-17T08:56:45.138943Z","submitted_at":"2025-01-13T02:47:49Z","title":"Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T20:57:20.935951Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2501.07021"},"observation_digest":"sha256:24c55dc3cf5533c35facfea27f43b75da86eeba1d8aa849931a0d8441e473be3","observation_id":"4a8ab5b4-d516-42e1-951d-5d6cb38d3d06","resolution":{"observed_at":"2026-08-10T20:57:20.935951Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-08-10T14:13:32.044702Z","title":"arXiv preprint arXiv:2410.02331 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.15579","last_updated":"2025-04-26T08:58:40Z","snapshot_observed_at":"2026-08-18T05:41:43.081942Z","submitted_at":"2025-01-26T16:07:11Z","title":"An Explainable Biomedical Foundation Model via Large-Scale Concept-Enhanced Vision-Language Pre-training","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T14:13:32.044702Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2501.15579"},"observation_digest":"sha256:cadba45253640938a8151d7fff82ab1057b6f9b31276e556a4605d37c536fbdf","observation_id":"031b3342-ace7-4e2a-bfb0-62304f324707","resolution":{"observed_at":"2026-08-10T14:13:32.044702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-08-07T00:49:51.013715Z","title":"Self-explainable ai for medical image analysis: A survey and new outlooks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12568","last_updated":"2025-06-14T16:52:04Z","snapshot_observed_at":"2026-08-18T14:46:10.953325Z","submitted_at":"2025-06-14T16:52:04Z","title":"MVP-CBM:Multi-layer Visual Preference-enhanced Concept Bottleneck Model for Explainable Medical Image Classification","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:51.013715Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2506.12568"},"observation_digest":"sha256:550f8e0f568c26949c063304ca630598a2162792d15dc83aeebd21e1c56dda75","observation_id":"12e4c531-5085-4fe3-b35b-1d37450ffbfc","resolution":{"observed_at":"2026-08-07T00:49:51.013715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-08-06T22:42:11.749811Z","title":"arXiv preprint arXiv:2410.02331 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20988","last_updated":"2025-08-19T03:06:01Z","snapshot_observed_at":"2026-08-18T02:28:59.589516Z","submitted_at":"2025-06-26T04:01:40Z","title":"Segment Anything in Pathology Images with Natural Language","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T22:42:11.749811Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2506.20988"},"observation_digest":"sha256:5c5c6f0c25422cec012783fe703adb00f24a525120b5c8d921f62b6645cde21b","observation_id":"7eeae1f6-43bc-4acc-a167-5b0d7004050e","resolution":{"observed_at":"2026-08-06T22:42:11.749811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-08-06T14:55:44.636105Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17303","last_updated":"2025-08-19T08:51:01Z","snapshot_observed_at":"2026-08-16T20:14:26.201673Z","submitted_at":"2025-07-23T08:09:42Z","title":"A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:44.636105Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2507.17303"},"observation_digest":"sha256:2e5e371b958dbe4265cf98b6ba0f56e6d3aa19b9f0100783cf9ceeeab433cac6","observation_id":"2fccdeb4-8804-4574-bab4-80d831e173a0","resolution":{"observed_at":"2026-08-06T14:55:44.636105Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-08-05T14:04:45.935553Z","title":"Self-explainable ai for medical image analysis: A survey and new outlooks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02597","last_updated":"2025-08-29T15:16:35Z","snapshot_observed_at":"2026-08-18T16:31:39.881804Z","submitted_at":"2025-08-29T15:16:35Z","title":"Solutions for Mitotic Figure Detection and Atypical Classification in MIDOG 2025","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T14:04:45.935553Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2509.02597"},"observation_digest":"sha256:8a5db70206b31374fd5f843911615c99b510368e56df33524908add2a8e2709e","observation_id":"2c9db953-63da-464e-a326-b83740ff6747","resolution":{"observed_at":"2026-08-05T14:04:45.935553Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":"2410.02331","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2410.02331 , year=","venue":null,"work_id":"9664a857-dafe-4077-8197-76783d98653c","year":2024},"citing_paper":{"arxiv_id":"2604.11700","last_updated":"2026-04-13T16:37:14Z","snapshot_observed_at":"2026-08-16T16:09:00.392086Z","submitted_at":"2026-04-13T16:37:14Z","title":"Exploring Radiologists' Expectations of Explainable Machine Learning Models in Medical Image Analysis","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-10T15:02:13.951049Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2604.11700"},"observation_digest":"sha256:dc8d9a7cade411278296a2b1d41d768d16e596be5cf5d67c12554158b6de98e2","observation_id":"8287f62d-451a-43ba-b324-932bd5a05607","resolution":{"observed_at":"2026-05-11T11:16:10.604366Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","version":2},"cited_work":{"arxiv_id":"2410.02331","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02331","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2410.02331 , year=","venue":null,"work_id":"9664a857-dafe-4077-8197-76783d98653c","year":2024},"citing_paper":{"arxiv_id":"2605.18681","last_updated":"2026-05-18T17:21:48Z","snapshot_observed_at":"2026-08-12T12:25:02.437849Z","submitted_at":"2026-05-18T17:21:48Z","title":"Learning Quantifiable Visual Explanations Without Ground-Truth","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-05-20T10:11:48.674949Z"},"links":{"cited_paper":"/paper/2410.02331","citing_paper":"/paper/2605.18681"},"observation_digest":"sha256:7be474311fd0707e9c516cf4a67f582af01ba985be7634bd33a2fe3753e33de3","observation_id":"4ac8f3c0-9e3b-42b1-9d78-eff30e2e5604","resolution":{"observed_at":"2026-05-20T10:13:11.859800Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.02331/citation-record","integrity":"/paper/2410.02331/integrity","json":"/paper/2410.02331/citation-record.json","paper":"/paper/2410.02331"},"outbound":[],"paper":{"arxiv_id":"2410.02331","last_updated":"2024-11-15T11:35:25Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T13:13:02.311775Z","submitted_at":"2024-10-03T09:29:28Z","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.02331."}