{"as_of":"2026-08-06T01:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:923a33e54fd32a777b766e4c1a6aa3bc88000752ef63c80ccfff45e9949155af","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T23:25:59.543194Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T01:23:24.624269Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.05382","snapshot_observed_at":"2026-08-02T01:23:24.624269Z","title":"Deformable attention graph representation learning for histopathology whole slide image analysis.arXiv preprint arXiv:2508.05382, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.14703","last_updated":"2026-07-16T08:04:25Z","snapshot_observed_at":"2026-08-02T01:23:21.566560Z","submitted_at":"2026-07-16T08:04:25Z","title":"Pretraining Multiple Instance Learning Networks with Multi-Teacher Distillation from Pathology Slide Foundation Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T01:23:24.624269Z"},"links":{"cited_paper":"/paper/2508.05382","citing_paper":"/paper/2607.14703"},"observation_digest":"sha256:502ac1d97809e900003b36ebf5912141834b222991bb42b023650166ee74f793","observation_id":"bdcffd2b-cd79-4b8f-bf2e-b3cf90e4a7a2","resolution":{"observed_at":"2026-08-02T01:23:24.624269Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2508.05382/citation-record","integrity":"/paper/2508.05382/integrity","json":"/paper/2508.05382/citation-record.json","paper":"/paper/2508.05382"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T23:26:00.384785Z","title":"Theory of Communication. Part 1: The Analysis of Infor- mation,","venue":null,"work_id":"a016587b-db20-4306-8385-a2c9ba00715b","year":1946},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.340137Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:a044c7357d63da683b4a42b356dcf79666c71fac41fed8b57fabf2eb98f279a2","observation_id":"04d9f114-87e0-4c9c-9804-551d29e54eda","resolution":{"observed_at":"2026-08-05T23:26:00.389788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.363178Z","title":"The Fractional Order Fourier Transform and its Application to Quantum Mechanics,","venue":null,"work_id":"b6045030-1005-4075-97f3-d7d7f93a4189","year":1980},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.345749Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:d8a10f681ef390d58759a1e92f31a1bfb92622774c0cf76a1193f3115ffd58f5","observation_id":"42a90030-d005-4522-ac67-b63b470037c3","resolution":{"observed_at":"2026-08-05T23:26:00.368365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.345642Z","title":"The Instantaneous Spectrum: A General Framework for Time-Frequency Analysis,","venue":null,"work_id":"6746cf7e-fde4-4007-83c0-06eaca993ce7","year":2018},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.351451Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:bf36f545d53672aefc49096f34940eb6d26d9c903b5247ad0baaf1cbb7c4695f","observation_id":"ad333d5a-3355-4ef9-93f0-a8b26f783073","resolution":{"observed_at":"2026-08-05T23:26:00.350354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.328202Z","title":"Flandrin,Explorations in Time-Frequency Analysis","venue":null,"work_id":"10950118-2804-4226-9d2d-571debc55861","year":2018},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.356418Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:92227f93af2b9fddc96c0f0fb0d7a28e1c346b683f8031d7527ff4c61c6afad4","observation_id":"8eb8881a-ea23-4f92-9996-9269b59f4361","resolution":{"observed_at":"2026-08-05T23:26:00.334051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.304871Z","title":"Recasting the (Synchrosqueezed) Short- Time Fourier Transform as an Instantaneous Spectrum,","venue":null,"work_id":"263cfa87-29e4-4a70-b88f-a7846fc84c7d","year":2022},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.361424Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:773a430604db222cd674e5169e0e67c0a360b18c2faaf2ca0b9d14a96711d6f6","observation_id":"4469db17-6e03-4e51-aa38-f90db8e44848","resolution":{"observed_at":"2026-08-05T23:26:00.314235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.283465Z","title":"Hilbert Spectral Analysis of V owels using Intrinsic Mode Functions,","venue":null,"work_id":"0f639e9c-1c15-4ad6-bad5-baa5363f9ea5","year":2015},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.366251Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:49338ad7273df75c9cd54fbb453edb0d084419a6f8ab76fdf812ae9b8860b4b5","observation_id":"44d05570-0786-4b06-8b4f-e61de4c8c37d","resolution":{"observed_at":"2026-08-05T23:26:00.290258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.261261Z","title":"ISA.jl: Instantaneous spectral Analysis in Julia,","venue":null,"work_id":"e4ab1cb1-bf2f-4dd0-a00f-4a9b605ded58","year":2022},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.371656Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:33c3d3e0ad82f2e991c5dcc657a32eaf0f30371de33bec67acb4713f52b84352","observation_id":"cd14148c-c9bd-497f-8a5f-414c003f4a85","resolution":{"observed_at":"2026-08-05T23:26:00.268838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.232352Z","title":null,"venue":null,"work_id":"ac735f13-d5bc-487f-a84a-4f2eb3f73a05","year":2001},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.376176Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:3a1d4ee49f2a0c8f139658460bd29a79a4789f38e155b2f1da81e99a054927ec","observation_id":"adbc2507-ee0b-490e-a415-bd9ae4dd12c0","resolution":{"observed_at":"2026-08-05T23:26:00.238127Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.212903Z","title":"Introduction to the Fractional Fourier Transform and its Applications,","venue":null,"work_id":"0bf65b2c-60eb-4e2f-9722-3f92b2155e85","year":1999},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.380799Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:0e46c3d350f478ae7f558b1d39b1ffde06ac05270872cfcc97fc36f71de03e33","observation_id":"204310f8-202c-448a-9c81-314ab5e6be3c","resolution":{"observed_at":"2026-08-05T23:26:00.218541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.191966Z","title":"On Namias’s Fractional Fourier Transforms,","venue":null,"work_id":"65c2e6ac-5ad0-4e96-8de7-20e9f139f43a","year":1987},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.385532Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:32e11d37922d3c7e9dac07a4fb659ef886751fea1833edaf8c03918facbd1a0b","observation_id":"f65f7b49-70eb-4c0a-9a05-04634f1a7859","resolution":{"observed_at":"2026-08-05T23:26:00.198137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.173234Z","title":"An Introduction to the Angular Fourier Transform,","venue":null,"work_id":"58cecb93-0bb5-4a39-9ceb-11471aca1eab","year":1993},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.390537Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:204dfb8ba3bef4c4d3aef19e2d447a7e70d9cd8e930973082e310aac5072b025","observation_id":"8673c825-458f-4e0d-98ef-80afd7f2c7fd","resolution":{"observed_at":"2026-08-05T23:26:00.178833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.152805Z","title":"Immersion of the Fourier Transform in a Continuous Group Of Functional Transformations,","venue":null,"work_id":"fcd01a40-1841-48e8-8b13-e3213bb32773","year":1937},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.395650Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:6bb972bd3a5a83e7c9932ac1fffe09ea3104c4b948e6699315f860ab533045a4","observation_id":"46add23b-6e9a-4c7e-b4bb-10816b0c8893","resolution":{"observed_at":"2026-08-05T23:26:00.158600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.133880Z","title":"A Unified Approach to Short-Time Fourier Analysis and Synthesis,","venue":null,"work_id":"08b6fd9a-9b2b-4f31-990a-274da20e595e","year":1977},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.401201Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:dd4c700072af963cc5b145498dc7d71ef4c463cca83831b7fab86be306cd79c3","observation_id":"6ade05d6-7eba-4ce5-b4da-22c0675ed3f0","resolution":{"observed_at":"2026-08-05T23:26:00.139842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.116824Z","title":null,"venue":null,"work_id":"7d5e8806-166d-4444-9fd2-f96556573e22","year":1987},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.406265Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:628a7e8db2debae2aff808856af1b335eed54dd44204d8b863a67da4ef8a8b07","observation_id":"0f08ba58-2adb-4e72-9738-3d6939aded10","resolution":{"observed_at":"2026-08-05T23:26:00.121727Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.091573Z","title":"A New Method for the Nu- merical Analysis of Non-Stationary Signals,","venue":null,"work_id":"9dd616d2-9ef4-4252-b641-fa811d8ba257","year":1976},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.411181Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:87851f2e7e109937ef00461e979ced1e0d8e21788eff0fdbb662e0f27fb44a2f","observation_id":"cc401fdd-59c4-4687-b4ba-2ef22ac18da9","resolution":{"observed_at":"2026-08-05T23:26:00.097298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.070737Z","title":"Analysis of Time-Varying Signals with Small BT Values,","venue":null,"work_id":"d27b2e77-f2af-469a-8aab-b56450da02cf","year":1978},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.416505Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:1303c41ef29c4d40cf98751045911a44e6daf877468800d301e08e6b3484a48d","observation_id":"713b82ef-3a1c-462f-80e5-1fdce856620e","resolution":{"observed_at":"2026-08-05T23:26:00.076658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.043786Z","title":"Synchrosqueezing Transforms: from Low- to High-Frequency Modulations and Perspectives,","venue":null,"work_id":"e3172140-d9f3-41d1-80a6-03a9d7bd0119","year":2019},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.421687Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:9bb30a70f09528e6a7a7f4ee38165dd44624ba4627ed6aa9e18befa707250aac","observation_id":"0a1b54f9-71c3-428f-9586-d15aba421bc6","resolution":{"observed_at":"2026-08-05T23:26:00.051445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:26:00.006178Z","title":"The Why and How of Time-Frequency Reassignment,","venue":null,"work_id":"353a0167-12d9-46ca-bfde-a14b1b8ee6d3","year":1994},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.427021Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:735c7b10ab3e9508b73dd65ce7ae96d38de662bb3e2edbc750d3fc66fa599d73","observation_id":"5f1a78e7-0bdf-4a81-b140-e3618d79f971","resolution":{"observed_at":"2026-08-05T23:26:00.021284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.987132Z","title":"Improving the Readability of Time-Frequency and Time-Scale Representations by the Reassignment Method,","venue":null,"work_id":"455a3791-02ef-464f-ba47-e29f0265b263","year":1995},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.431664Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:3ff018e2ba946a15c4d078ef8b409a7af4b6087a7172c298d2c727d9024f5837","observation_id":"937e8e50-23ee-4987-8df4-67117840473a","resolution":{"observed_at":"2026-08-05T23:25:59.992176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.968994Z","title":"Time-Frequency Reassignment and Synchrosqueezing: An Overview,","venue":null,"work_id":"b17114f9-bdff-46ca-8683-d2d2ccd4a2f6","year":2013},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.437468Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:2d45a413fb7259161c558c789b87ce16064b1e031e2e28cb8739b667867451a7","observation_id":"58d5031c-bcfc-4180-a1d9-cc7c7816f0ec","resolution":{"observed_at":"2026-08-05T23:25:59.974428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.949067Z","title":"Novel Short-Time Fractional Fourier Transform: Theory, Implementation, and Applica- tions,","venue":null,"work_id":"dc21d3c9-1ca4-4dcb-9118-9904f7aaf242","year":2020},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.443339Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:5541101987fc47a6f9acc3d514f5d656559ce6621a53d2ab2c619c59a884f2f8","observation_id":"2f1804ef-0ca8-414f-b3d8-aea2770f41ed","resolution":{"observed_at":"2026-08-05T23:25:59.956034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.929436Z","title":"Bracewell,The Fourier Transform and Its Applications","venue":null,"work_id":"33a2db09-9c68-4550-afb2-78278ca6352b","year":1980},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.448273Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:94c2dd42f6b54d5341e6e01891bad9ade0619dfb3a9fe1a8e1d27d54938acd5f","observation_id":"fde16b98-6e9a-4cce-8f04-dfc2fae3759c","resolution":{"observed_at":"2026-08-05T23:25:59.934580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.910508Z","title":"The Chirplet Transform: Physical Considera- tions,","venue":null,"work_id":"d743712f-82d1-4a98-9ca1-e912e3084b75","year":1995},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.453255Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:c5ec4ae16d83affbcd4deaa49ce51a8af0b04d8eb648619335e9b2ff0df87084","observation_id":"9b2a807f-4290-4232-87ff-9f05723fc6b4","resolution":{"observed_at":"2026-08-05T23:25:59.916619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.893416Z","title":"Robinson,Non-Standard Analysis","venue":null,"work_id":"a705dd9f-e744-45c9-b704-2e314386bbcd","year":1974},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.458566Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:f8e59d222830b0a077c755c44dbb60d4693dae885a5f5eccaf3ba308ed0e8164","observation_id":"b12dcdf6-56fb-4010-9f7c-7ac4f801a986","resolution":{"observed_at":"2026-08-05T23:25:59.898876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.875711Z","title":null,"venue":null,"work_id":"9fe94644-3dd6-4f87-b55e-65dfbd958dc2","year":2009},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.464355Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:ccf5338f00e4329d9f9ea48b29d3197e8461697c46655774edbd1557352a2e9a","observation_id":"f4f20424-9dc5-498f-9baa-0bba307d31f3","resolution":{"observed_at":"2026-08-05T23:25:59.880215Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.856738Z","title":"Theorie et Applications de la Notion de Signal Analytique,","venue":null,"work_id":"9281d350-e0c5-4939-bcc4-550a55e9d6dd","year":1948},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.469426Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:9b009dc391eab11849121209250eaf2edcc3e36a21a1418b3aa1ff54610cefac","observation_id":"2ed83dff-3422-4828-9f2a-ed0ac40f3402","resolution":{"observed_at":"2026-08-05T23:25:59.862709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.839797Z","title":"The Analytic Signal Representation of Modulated Wave- forms,","venue":null,"work_id":"2ab5f82e-4372-4e85-a2e3-77d98579afda","year":2071},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.474676Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:17db4d74f160057ee830107f0a15a5491c03d6c1cf5ff4710b724806383a3843","observation_id":"03d081e6-313e-46d2-b2a8-eade66b19341","resolution":{"observed_at":"2026-08-05T23:25:59.844823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.820913Z","title":"Cohen,Time-Frequency Analysis","venue":null,"work_id":"5a92855b-90ef-47a7-9b57-53063eb85a43","year":1995},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.481292Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:7386514d3cc64fc9264e3ce303c8226e74bbeb7a8e986f2294e936a039da4748","observation_id":"01dfedad-9699-4396-93e7-ec52543ce2dc","resolution":{"observed_at":"2026-08-05T23:25:59.826251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.802569Z","title":"On Analytic Signals with Nonnegative Instantaneous Frequency,","venue":null,"work_id":"91b010e9-676d-4dd5-9d2c-3777ef068c9e","year":1999},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.486410Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:045ea8813eeaa5c8db1ae2c7196e284ba4c63f694c87e2b1a4f15be732be072a","observation_id":"d67bac12-0cbb-4876-9410-937e23ea1441","resolution":{"observed_at":"2026-08-05T23:25:59.808056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.783730Z","title":"Boashash, Ed.,Time Frequency Signal Analysis and Processing","venue":null,"work_id":"0add03f8-9e79-4d40-a57e-8cdbaba0011c","year":2003},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.491591Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:5061fbf007ce9175ab776d9b1f7db4e34c8f29d52df469e5799cf392a37bd89f","observation_id":"429e07d5-6bc3-44a1-94e2-d4366f7562ed","resolution":{"observed_at":"2026-08-05T23:25:59.789131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.763915Z","title":"Papandreou-Suppappola, Ed.,Applications in Time-Frequency Signal Processing","venue":null,"work_id":"ce778ce1-7718-4cad-9799-a64a46c88e00","year":2002},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.495999Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:fbb4e451df18f773b211a0cf89d12707e9a47b572765ea0a5d7776fe7e22ed2e","observation_id":"ba643eb4-39ca-4c41-9a75-8b8ed3f5ba9f","resolution":{"observed_at":"2026-08-05T23:25:59.769580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.745554Z","title":"Stankovi ´c, M","venue":null,"work_id":"e42f9be9-5863-4367-a9e6-40fa133ee168","year":2014},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.500606Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:704db09b3d2dbf49979aad2a4bd3a39dc169500fda223873c0a36355a37535c3","observation_id":"39546a63-3eb4-4342-9a75-b39b905f329a","resolution":{"observed_at":"2026-08-05T23:25:59.750923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.728343Z","title":"Boashash,Time-Frequency Signal Analysis and Processing: a Com- prehensive Reference","venue":null,"work_id":"a7d2fe3a-6e58-46be-ab47-53b880143780","year":2015},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.505099Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:f762005cc265a5476dc753506f3832e6e6cfd04790e034e9c55ec521d9fc03cf","observation_id":"f7ff0865-1acb-448d-b790-3dc95d08b8f9","resolution":{"observed_at":"2026-08-05T23:25:59.733161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.712353Z","title":"Gr ¨ochenig,Foundations of Time-Frequency Analysis","venue":null,"work_id":"f8627b33-7f96-446d-8168-fc6c03399d58","year":2001},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.509915Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:a75be56608b0b5b6a8f6eb26d0dc8218fd9da42d207edab38c518ea5ea206eab","observation_id":"bc761315-f764-47fa-a962-6b0874231400","resolution":{"observed_at":"2026-08-05T23:25:59.717204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.695914Z","title":"Time- Frequency Super-Resolution with Superlets,","venue":null,"work_id":"fcf5292c-35b3-458b-8e72-b3262d095a32","year":2021},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.514902Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:02f79c9c37abc827eb4546e4678630454da418c08eb7f8b60bbe2a2dbf2c199f","observation_id":"da4f29fd-7344-413d-9f99-f33095638645","resolution":{"observed_at":"2026-08-05T23:25:59.700901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.677575Z","title":"Hlawatsch and F","venue":null,"work_id":"7c95b363-db76-4e88-b78d-4c14e9a6f1ab","year":2013},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.519805Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:81ad9d8cbea6e5c04a1e39f924ee29afd89f23596a0e1a4cae438fa05cf4510b","observation_id":"ba0ec0e1-0f89-40f6-8473-06f1e14157df","resolution":{"observed_at":"2026-08-05T23:25:59.683821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.657279Z","title":"Carmona, W.-L","venue":null,"work_id":"9dcf88db-d52e-46fb-918f-efabcc220387","year":1998},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.524278Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:80241563c3560ce9c6ff081179393cdf2d6cb277481c41be821dc5bace8bf0cc","observation_id":"5112f511-3853-4686-bad0-44d8ae8fa91f","resolution":{"observed_at":"2026-08-05T23:25:59.662779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.639252Z","title":"Flandrin,Time-Frequency/Time-Scale Analysis","venue":null,"work_id":"3a0bcb6f-4df5-41b4-9005-d190460ca4fc","year":1998},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.528705Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:709d6c3bbf761949b803f114c7f75dff5ecde4414aa3a6bdaaba5dfb970014dd","observation_id":"1670913e-9fc1-4fa8-a9a8-0c4a57052efd","resolution":{"observed_at":"2026-08-05T23:25:59.644272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.615651Z","title":"Mallat,A Wavelet Tour of Signal Processing","venue":null,"work_id":"dfc372a4-ea91-4c09-9ee4-6a4c0dda527a","year":1999},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.533569Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:84803679a2d01466ea45ec8e20a9cd1e308a8bd831bbc9333713210b933430ff","observation_id":"3c663044-6cf5-468d-b2bb-dc8d1a27b208","resolution":{"observed_at":"2026-08-05T23:25:59.621090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.598335Z","title":"Br ´emaud,Mathematical Principles of Signal Processing: Fourier and Wavelet Analysis","venue":null,"work_id":"49c9f728-0f87-48de-af57-072735eac471","year":2002},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.538407Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:0e889bfdbd3b642049ef26389bb25bb15c7d3fa6ba8852bc68b9d46dd9558e75","observation_id":"8864a679-6cae-4f82-8193-358db53dbce6","resolution":{"observed_at":"2026-08-05T23:25:59.603400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-08-05T23:25:59.578801Z","title":"Meyer,Wavelets: Algorithms & Applications","venue":null,"work_id":"aefd9ed3-f890-46bf-86a0-080765ac46a3","year":1993},"citing_paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T23:25:59.543194Z"},"links":{"citing_paper":"/paper/2508.05382"},"observation_digest":"sha256:9ce95e41810058adcf984440470bfcf89dc3bb60849b9384ebf6605ec661a02a","observation_id":"679512c7-ac99-45ca-9a5b-d57ac33f1bb9","resolution":{"observed_at":"2026-08-05T23:25:59.585670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.05382","last_updated":"2025-08-07T13:30:29Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T23:25:57.303404Z","submitted_at":"2025-08-07T13:30:29Z","title":"Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":38},"total_outbound_references":41},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2508.05382."}