{"as_of":"2026-08-13T05:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1479b094d432366a0c52a25de7857f91e5a83a287d2fc0161ff9fa7c3c4455fd","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:18:17.334955Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2507.03341/citation-record","integrity":"/paper/2507.03341/integrity","json":"/paper/2507.03341/citation-record.json","paper":"/paper/2507.03341"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:18:17.923475Z","title":"Nature communications 10(1), 1400 (2019)","venue":null,"work_id":"6fb54079-bc48-4a9e-b9bf-106512ae9fb7","year":2019},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:16.874919Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:d6dfd81e7e7a5b12a727e1c40632d358e7f66dc534c4097f40cf3295268ea17a","observation_id":"d0ea0e4d-3829-4d8c-adcb-ffc19bf16d68","resolution":{"observed_at":"2026-08-06T20:18:17.927829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.910277Z","title":"Nature methods19(8), 1004–1012 (2022)","venue":null,"work_id":"4621fd77-4da6-4eeb-8314-0a95f1543c9c","year":2022},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:16.897063Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:a047d6977919cedf85a3fbecf991b784040d9b07c44353f19f07fd7ba3337119","observation_id":"975e3668-aab5-46b4-99d1-37bae2ab0ed4","resolution":{"observed_at":"2026-08-06T20:18:17.914265Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.896133Z","title":"Proceedings of the National Academy of Sciences 117(25), 14453–14463 (2020) Detail-Enhancing Generative Adversarial Networks 11","venue":null,"work_id":"54a98e8f-3d07-4871-bc2a-c6a2b68156c4","year":2020},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:16.919279Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:18f4c24ed09623c6757d26d4f392944919d3b881381bd4402d264a8d60d77b2e","observation_id":"978663a1-5452-46c8-9569-af0514fc5575","resolution":{"observed_at":"2026-08-06T20:18:17.900686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.881096Z","title":"Nature Protocols 16(7), 3547–3571 (2021)","venue":null,"work_id":"d0b4638e-8882-4963-a9c2-5b0da6db10c9","year":2021},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:16.943685Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:0e9f5ffb0cda6ce101257751e64a224e9e22ec5123d6013122b5eaa03e4ba6c6","observation_id":"79d6ca7e-2e56-4c0c-a16e-a53ee0718f60","resolution":{"observed_at":"2026-08-06T20:18:17.885771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.867269Z","title":"Nature communications 12(1), 1080 (2021)","venue":null,"work_id":"0e47f302-6f7c-4684-8031-059ff705463a","year":2021},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:16.980553Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:3af5730bd75b575b1e5ef4d87ea3fcf230df71cf514f49ecba91dc2effc37971","observation_id":"eccf6a73-c041-48f2-8073-60a6978b5bd1","resolution":{"observed_at":"2026-08-06T20:18:17.871611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.852856Z","title":"Science translational medicine9(411), eaah6756 (2017)","venue":null,"work_id":"c8e9f626-d661-42a5-a0d1-ef4d6f941f18","year":2017},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.003948Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:863faa7a26fca7f5f8c40cf200aafb9782081090cd37581cf6d3f1d67a68e980","observation_id":"18f55d78-8eed-4ae3-b458-592f951289bf","resolution":{"observed_at":"2026-08-06T20:18:17.857880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.839162Z","title":"In: 2016 IEEE International Ultrasonics Symposium (IUS)","venue":null,"work_id":"c7cebf87-0315-4988-8e8a-f5c08f08bd5f","year":2016},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.026609Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:760afd22b306ff733bc096d21efebd544eb41a848337963f6b0b334ff5f5cec9","observation_id":"36f931df-faab-4cc3-9e91-a582b1bf9c06","resolution":{"observed_at":"2026-08-06T20:18:17.843449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.823604Z","title":null,"venue":null,"work_id":"139f6e70-8e85-4a36-be22-e1e4651a0890","year":2017},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.057491Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:6ab4cf303e24571f75a6bc49e6e37af4531b1c200aa231d09f902d45fdf0386b","observation_id":"cc0270e7-8a63-4f9a-8a88-da8cf3e4a44a","resolution":{"observed_at":"2026-08-06T20:18:17.828326Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.808630Z","title":"Frontiers in neuroscience13, 1384 (2020)","venue":null,"work_id":"79bf28d1-5825-444a-8938-a4cf557be787","year":2020},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.085177Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:df7c3d71ec77fdc61306c608d5a7fa94423523ead52ec3d0a5aa3e96619f37f5","observation_id":"4afe04dd-c47c-418c-a533-e513a60a2dcf","resolution":{"observed_at":"2026-08-06T20:18:17.813125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.794392Z","title":null,"venue":null,"work_id":"6fbc49c9-fbfc-4a4b-9a98-f760130270d9","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.112935Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:8e0fc26c4c4e50941b6d2faf3a858d9a5e335c9345fd2e9d4b04f48d82c3057d","observation_id":"696955b6-0e6d-4b9d-a28e-81343704a95e","resolution":{"observed_at":"2026-08-06T20:18:17.798936Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.779265Z","title":"Nature Neuroscience27(1), 196–207 (2024)","venue":null,"work_id":"f51adddb-1101-4acc-9958-8cdd5345f46f","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.128158Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:f0d462c727e8bc5075e600571b47816b9f99194b12062ec3ec1b3bd90cbdabf4","observation_id":"042c7450-eff9-48ba-8896-f553878da392","resolution":{"observed_at":"2026-08-06T20:18:17.784027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.764500Z","title":"Re- search 6, 0200 (2023)","venue":null,"work_id":"1b48b2b9-079c-43bf-a31d-571fcac0daf4","year":2023},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.143213Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:5122d0d690149e12efc5300011b242f17ec996ad74e5751c30f974cb1f7605f5","observation_id":"c8acd450-ef89-435f-9f2b-a2bf693e00cf","resolution":{"observed_at":"2026-08-06T20:18:17.769073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.750370Z","title":"Neuron112(10), 1710–1722 (2024)","venue":null,"work_id":"d040c869-4da6-41f2-a32a-cf58adfb97dc","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.193997Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:0c1e3dd5c3834322d667504a38e0f11a29e609245970022e298995892c6f9c21","observation_id":"3720be5c-ece2-4a66-b36d-fa0f5f619be3","resolution":{"observed_at":"2026-08-06T20:18:17.754537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.736493Z","title":"Advances in neural in- formation processing systems27 (2014)","venue":null,"work_id":"4a7ab50d-4b15-412b-87d3-5696af6396c5","year":2014},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.228901Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:38b59821dd0a025e0ba43f75185f76ee4040be26636b9d37ad3dd56141e5b228","observation_id":"d254e1e5-24bd-44a1-ae3e-b8b686995dc1","resolution":{"observed_at":"2026-08-06T20:18:17.741206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.723276Z","title":"Science Trans- lational Medicine 16(749), eadj3143 (2024)","venue":null,"work_id":"a65b7ac5-b17f-4c3a-a04c-41322efbadb1","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.234026Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:ad064b60a592e1486dda34560c1dcb9712f82cef5c0b9bcb0d181eb6ea632314","observation_id":"7faf0b86-e9c1-4dfe-84e9-280b29a5a952","resolution":{"observed_at":"2026-08-06T20:18:17.727422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.709438Z","title":"Brain imaging and behavior15, 276–287 (2021)","venue":null,"work_id":"e1f9c218-3f90-4512-b043-be231281a0b6","year":2021},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.238050Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:735aa8a97e3ff45b98dbcc0686902ba205cdfcbedffc6ccff8ee92f3d4f6f4a0","observation_id":"8921de31-d8a9-4c67-9642-7d9d0d640000","resolution":{"observed_at":"2026-08-06T20:18:17.714188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.695165Z","title":null,"venue":null,"work_id":"8ee5c177-61c2-46b2-99bd-be349738939f","year":2025},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.242354Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:0793d6b3b1fabb3f0ce8701e7dd5825fe3fccd2da184b0ce3ed578bab75dfcc7","observation_id":"8ff084f6-057b-43ab-8d75-fb2d88b563a6","resolution":{"observed_at":"2026-08-06T20:18:17.699159Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.679202Z","title":"In: 2018 International conference on artificial intelligence and big data (ICAIBD)","venue":null,"work_id":"4969ce06-52c2-453e-a073-b3025c825475","year":2018},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.247442Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:7fb8448c6b4ed0f50ab12318e620af5890e5078e8308ac45041336d3c41acba0","observation_id":"c2c155e5-0a03-4bfb-9c9a-efe61b82e440","resolution":{"observed_at":"2026-08-06T20:18:17.683767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.665375Z","title":"Scientific Reports13(1), 12098 (2023)","venue":null,"work_id":"14d0bfbf-7309-4a6a-8c66-9a34c837f719","year":2023},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.251626Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:54a29a37aadbb595e7709ca94d1c4eb6c7a4042b04533a27dc056f9907250043","observation_id":"64aaefc9-9ca4-4a6b-a2a1-04c09b435270","resolution":{"observed_at":"2026-08-06T20:18:17.669608Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.650682Z","title":"Procedia computer science111, 17–23 (2017)","venue":null,"work_id":"4e207f93-5068-4358-865d-5b177b364c69","year":2017},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.255808Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:dd1bb0374192966429a7196f4bd3c3aec4946b6fed4598ed31be874af1f8c255","observation_id":"06f8c028-97e3-40c1-be91-fe7f61c2d4c0","resolution":{"observed_at":"2026-08-06T20:18:17.655309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.637243Z","title":null,"venue":null,"work_id":"6c1aa367-278b-433e-8dbb-390b1c45994f","year":2009},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.260544Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:e6059eaeb0f8df83d9795618f788b78dfc19aae23e8bf7c2bb5c387b1d2a3da2","observation_id":"ac53dab8-c8af-4693-9873-c425e4b8bfef","resolution":{"observed_at":"2026-08-06T20:18:17.641464Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.622596Z","title":null,"venue":null,"work_id":"e4ca946f-53c2-4bbf-939a-5fac7f74f339","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.264487Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:33144e9f4b3a6b653ee1144e17953c4b4f861e61afb6ca3fe6105a1055889707","observation_id":"9a83d1d5-884f-4836-97d5-8d67753b19d2","resolution":{"observed_at":"2026-08-06T20:18:17.627539Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.607461Z","title":"Deep learning applications pp","venue":null,"work_id":"9591f258-d14a-4386-b05d-996780ada616","year":2020},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.268758Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:4f7f9a29eb1121bacaadc9f28b073fe339b46064f5093cdfb262beaafbf813ad","observation_id":"84006c1a-41d7-458c-b6db-3baf27e4a8f4","resolution":{"observed_at":"2026-08-06T20:18:17.611835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.592115Z","title":"IEEE Transactions on Circuits and Systems for Video Technology (2025)","venue":null,"work_id":"cdae0450-1496-4355-a569-9cc04cbe0b15","year":2025},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.272870Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:868cd03147c0cc7c8ba13c39ed83713dabebe4f41074deb524411b0ead9eb8a1","observation_id":"9a28fe98-a6d3-45af-a8f4-c5cc803b4b44","resolution":{"observed_at":"2026-08-06T20:18:17.597222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.570240Z","title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering31, 4601–4612 (2023)","venue":null,"work_id":"25f49224-64a2-4d2f-a0c0-2090b7ea1287","year":2023},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.278146Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:325be9a1c506c8121f0160a37e13eba7f952ec7ee1fdf1f1aef1859de9412096","observation_id":"88adbb9f-056d-4fea-aba8-c620c38ad339","resolution":{"observed_at":"2026-08-06T20:18:17.577746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.553437Z","title":"IEEE Transactions on Cybernetics54(6), 3652–3665 (2024)","venue":null,"work_id":"89b0b326-eab4-4234-bd9f-df16b944b22f","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.282612Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:783f1490c7a41d6ed56db4059c0327e32fa70dcc34a76b4997760dc417378e05","observation_id":"8dd12e55-afbf-4605-9bd4-608463ce4527","resolution":{"observed_at":"2026-08-06T20:18:17.558179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.533692Z","title":"In: Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, October 29–November 1, 2021, Proceedings, Part III 4","venue":null,"work_id":"0ac5857b-5ec1-49b8-82d4-ef3d85b96fff","year":2021},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.287437Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:10f968d0ab20362eb01a29d80e788caf11bdffa4e4c85a12f7cf9a57a04ad01a","observation_id":"a0981bb0-4c68-4f25-ae93-f88bbc5ab74a","resolution":{"observed_at":"2026-08-06T20:18:17.539932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.515510Z","title":"In: Medical imaging with deep learning (2022)","venue":null,"work_id":"7ef91c6c-71b9-4b29-88a2-cf9ebd93ec3e","year":2022},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.291857Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:2e6d1484d4517eff10eaa871dd17b4c819852f618d1303f0985ed1332bb484cb","observation_id":"721dba0e-520d-4b48-ac65-dc62e464c2a6","resolution":{"observed_at":"2026-08-06T20:18:17.520566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.496774Z","title":"In: Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, October 29–November 1, 2021, Proceedings, Part III 4","venue":null,"work_id":"477f529d-1b67-42f1-a696-be2fc1411bc2","year":2021},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.296752Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:2ba1c598ff745e39038b0710377dc24f76af3760cf93e3abfe84324b75afbfe4","observation_id":"bb960909-7336-40be-8fde-3fe7a1276bb6","resolution":{"observed_at":"2026-08-06T20:18:17.502451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.480658Z","title":"IEEE Transactions on Pattern Analysis and Machine Intelligence (2024)","venue":null,"work_id":"77fb39b8-db99-48eb-bf6c-c15926a68dba","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.300948Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:aa52d3692b02e3491f0f0c95263e403a8d5b38c2619cdd71abcda55841cb386a","observation_id":"72497445-0a16-4601-9222-0798030dfb7a","resolution":{"observed_at":"2026-08-06T20:18:17.485846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.465305Z","title":null,"venue":null,"work_id":"b2cc69b7-9104-4ab2-b152-17ad4409f69b","year":2023},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.304791Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:7ef37e1c47dd8d7bfb158ed276bee7d157773c44ccf8d5ea78a9ae191c545ea1","observation_id":"9e6bd4fa-503a-4a89-b6cd-a9a1d8bef0e0","resolution":{"observed_at":"2026-08-06T20:18:17.469569Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.450810Z","title":"IEEE Transactions on Cybernetics54(9), 5026–5039 (2024) Detail-Enhancing Generative Adversarial Networks 13","venue":null,"work_id":"d43385cf-2fb3-4a2e-9664-0e7bfaa41cbc","year":2024},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.309133Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:bf564ea4c5f89a127a5669dc61cbf886d0d4606aba96891b682208bb622f25e0","observation_id":"000d8eb8-5122-427a-b71d-ad2929dadd23","resolution":{"observed_at":"2026-08-06T20:18:17.455600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.436009Z","title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering31, 4017– 4028 (2023)","venue":null,"work_id":"4b6e53e2-e62e-4ac7-86bc-234090a83e8c","year":2023},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.313397Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:df216b6c99384d1bbaea68feebbe24812268fb635fd8be5c885dcdd388bb21c9","observation_id":"908b2982-46ff-4d8a-893a-6baa47565a4e","resolution":{"observed_at":"2026-08-06T20:18:17.440684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-06T20:18:17.317613Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.317613Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:1dd891816000f47df420df4263388c30ab382b7698caefe74ca212d56afdb728","observation_id":"bfbb7307-8f04-47e3-9b85-1cad0e66ec7d","resolution":{"observed_at":"2026-08-06T20:18:17.317613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.11096","last_updated":"2019-02-25T21:32:06Z","snapshot_observed_at":"2026-07-06T07:04:57.275371Z","submitted_at":"2018-09-28T15:38:49Z","title":"Large Scale GAN Training for High Fidelity Natural Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.11096","snapshot_observed_at":"2026-08-06T20:18:17.321585Z","title":"arXiv preprint arXiv:1809.11096 (2018)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.321585Z"},"links":{"cited_paper":"/paper/1809.11096","citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:fcbcae8ec269c56afe1e6059cc44cd76380b6a8906ce1ced3d02a40f36fc2f45","observation_id":"fc5c5f9c-bb8d-4400-af77-026e324de654","resolution":{"observed_at":"2026-08-06T20:18:17.321585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:18:17.326282Z","title":"In: ACM SIGGRAPH 2022 conference proceedings","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.326282Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:2174b53fb5966a32f400562d8bfce5316576bef7e9bf0e142e9d2836c515732b","observation_id":"ee11e284-8792-454e-903f-006914a15e9f","resolution":{"observed_at":"2026-08-06T20:18:17.326282Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.04627","last_updated":"2022-06-05T01:57:58Z","snapshot_observed_at":"2026-07-06T11:56:10.689708Z","submitted_at":"2021-10-09T18:36:00Z","title":"Vector-quantized Image Modeling with Improved VQGAN","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.04627","snapshot_observed_at":"2026-08-06T20:18:17.330595Z","title":"arXiv preprint arXiv:2110.04627 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.330595Z"},"links":{"cited_paper":"/paper/2110.04627","citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:2504caeacff1bc14a22a6f29dc78aacfef88ff236e24409f3579bb2033df3572","observation_id":"524acdae-8e86-4b37-a536-90fc9e534ecc","resolution":{"observed_at":"2026-08-06T20:18:17.330595Z","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":"2026-08-06T20:18:17.400905Z","title":"In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition","venue":null,"work_id":"a8042307-09a7-46f2-840d-d50254f456b3","year":2020},"citing_paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:18:17.334955Z"},"links":{"citing_paper":"/paper/2507.03341"},"observation_digest":"sha256:035466cd4e6cf1dba11bbad75791ead18fa363c68792e3602fafca390e59387b","observation_id":"d4fb18bd-141a-440b-8b51-06ed439647e6","resolution":{"observed_at":"2026-08-06T20:18:17.406615Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.03341","last_updated":"2025-08-19T15:26:02Z","latest_version":2,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-11T05:47:33.914784Z","submitted_at":"2025-07-04T07:00:41Z","title":"UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":0,"verified_fuzzy":28},"total_outbound_references":38},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.03341."}