{"as_of":"2026-08-17T13:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8ed62caa45fcbf2829aa98d81399a53c43e38f7d562e9edb49c5f887f25f8bef","coverage":[{"denominator":50,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":50,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T10:40:50.360290Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2504.17628/citation-record","integrity":"/paper/2504.17628/integrity","json":"/paper/2504.17628/citation-record.json","paper":"/paper/2504.17628"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.152925Z","title":"Diabetic Foot Ulcers: A Review,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.152925Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:009d82d0e5b24d095b57b49afe79129fd3d39931a88b5bf5422f7cc0110b8d54","observation_id":"ba16c8e7-f1f9-47ab-a66b-161530d6a8cd","resolution":{"observed_at":"2026-08-16T10:40:50.152925Z","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":"10.1056/nejmra1615439/suppl_file/nejmra1","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.648351Z","title":"Diabetic Foot Ulcers and Their Recurrence,","venue":null,"work_id":"5e832d14-247c-4237-88a8-1148d445c556","year":2017},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.157925Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:ad0302d1da84ef654b73a764b25a64d381ef09a556add59196876b2f45abf9b7","observation_id":"44ad7af4-348e-4432-acb5-255b1dd2cf1f","resolution":{"observed_at":"2026-08-16T10:40:50.652160Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.162110Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.162110Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:9b8c2942a39e0aed9e8de930ed07b6b24daf35d621ea10e3ef85e56115ef2b42","observation_id":"02ba8824-26d9-4963-96cc-a8b26198b0c5","resolution":{"observed_at":"2026-08-16T10:40:50.162110Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1177/19322968231187660/asset/images/lar","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.628892Z","title":"Diabetic Foot Ulcer Imaging: An Overview and Future Directions,","venue":null,"work_id":"a48ff227-bab9-43d9-9328-8ca19b0f23dd","year":2023},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.167108Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:2b2e2a439353616a21d45244296a7be8bf51614fb01101630e2410d2d49fbfef","observation_id":"1f925697-2e57-43a9-93b7-b47729a9fc04","resolution":{"observed_at":"2026-08-16T10:40:50.632513Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.171378Z","title":"Recognition of ischaemia and infection in diabetic foot ulcers: Dataset and techniques,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.171378Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:4406e41d98106b75133a9b5ebb78783a50dc316648f29a0bfaecd7bb2f05ab35","observation_id":"5a163afe-b632-42d9-8de7-06bf0f664bab","resolution":{"observed_at":"2026-08-16T10:40:50.171378Z","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":"2026-08-16T10:40:50.176137Z","title":"Is my wound infected? A study on the use of hyperspectral imaging to assess wound infection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.176137Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:ced6344dd0c3a8d28e017e9e66262d4d1c8bdf1aa82a56e17e93524f381c4e2b","observation_id":"84211e37-7413-4ece-8055-d6460f5512f8","resolution":{"observed_at":"2026-08-16T10:40:50.176137Z","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":"10.1177/0141076816688346","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.618557Z","title":"Prevention and treatment of diabetic foot ulcers,","venue":null,"work_id":"43ff26b8-5248-49f9-bb45-5a595a566d57","year":2017},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.180581Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:84012489f317ddd859dc37fb2ba129442e6a188f855ecbf3ad1949b4c19281f0","observation_id":"e176dc71-2e70-4d64-883d-13d4c0ed12b8","resolution":{"observed_at":"2026-08-16T10:40:50.621962Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/cosmetics11060218","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.604574Z","title":"AI Dermatochroma Analytica (AIDA): Smart Technology for Robust Skin Color Classification and Segmentation,","venue":null,"work_id":"9a9b6d2e-0da7-4634-b82c-5a57807d5d0f","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.185236Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:38d099cf599eacfe0e1ac537986f5d2a09cc180515b90d5aa15715cc7a7b7f97","observation_id":"e06fda84-b5ac-4e36-bc1b-beb7ce5b24ea","resolution":{"observed_at":"2026-08-16T10:40:50.609099Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.4239/wjd.v7.i7.153","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.593468Z","title":"Diabetic foot disease: From the evaluation of the ‘foot at risk’ to the novel diabetic ulcer treatment modalities,","venue":null,"work_id":"3e4396f9-cca5-4e1c-a93c-eb5028fa423e","year":2016},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.189936Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:68cf3c6ca20c01e903d54f134cb15ffe3673db3e0aa89494e00f8ff2b0514b42","observation_id":"5d10410e-a8f5-448b-8b4a-b08ffc1c133e","resolution":{"observed_at":"2026-08-16T10:40:50.597224Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.2337/dc17-1836","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.582055Z","title":"Current Challenges and Opportunities in the Prevention and Management of Diabetic Foot Ulcers,","venue":null,"work_id":"112b4c00-ac5c-4969-946a-1ef595d5f356","year":2018},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.194758Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:7f5d7f33a48cb44b3498eb8ca0cb08fc9bfde849c49593dc2f64f1368a8420e7","observation_id":"9cb92adf-f244-472c-8f68-70a62b498a63","resolution":{"observed_at":"2026-08-16T10:40:50.586078Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/s0891-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.570678Z","title":"WHO IS AT RISK FOR DIABETIC FOOT ULCERATION?,","venue":null,"work_id":"10d4a70d-83cc-45f1-add7-efe7faa7ac26","year":1998},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.199107Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:b500d4811c3a3bb5fc46f61c0761f63f0c3a705689734a700d07a20498dafb8e","observation_id":"122bba0c-f654-426e-86d4-0c7b24f657a5","resolution":{"observed_at":"2026-08-16T10:40:50.574660Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1136/bmjdrc-2020-001815","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.558950Z","title":"Quantifying dermal microcirculatory changes of neuropathic and neuroischemic diabetic foot ulcers using spatial frequency domain imaging: a shade of things to come?,","venue":null,"work_id":"b93c62bc-41e2-479d-bfa6-4541a7e36f60","year":2020},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.203642Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:cf5abd8f72a350d711d02fd3c428b8e640650c0cb118f16ae7504bda3ad437fe","observation_id":"d876c31d-8ff6-49de-8cfd-6368385ee241","resolution":{"observed_at":"2026-08-16T10:40:50.562506Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.208629Z","title":"Deep learning in diabetic foot ulcers detection: A comprehensive evaluation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.208629Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:dae8d53cb91ba6d67cbb49836a75d53cd7f548858ac96bcc7101495303b5c9f4","observation_id":"95b29951-5d61-4a24-8444-c802e05f342a","resolution":{"observed_at":"2026-08-16T10:40:50.208629Z","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":"10.1016/j.jtv.2024.07.004","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.548380Z","title":"The impact of machine learning on the prediction of diabetic foot ulcers – A systematic review,","venue":null,"work_id":"d23608b9-5b5b-45c3-b194-20e3784c2d65","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.212628Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:dde8d29f0544b88a5a43757ab39e3d3d0d644d16b01557d107c1298f2298b833","observation_id":"ba88d161-6547-4d4b-9160-ba79b18b060e","resolution":{"observed_at":"2026-08-16T10:40:50.551798Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s42979-024-02981-4/figures/12","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.537446Z","title":"Automated Detection of Infection in Diabetic Foot Ulcer Using Pre-trained Fast Convolutional Neural Network with U++net,","venue":null,"work_id":"cf556a80-cb82-4d06-aa0d-eb92350fa916","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.217258Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:148bd67c8c9da76a468dec400122f212c6e9d98d2ded755ab08b905c84e20cb6","observation_id":"26c3462d-49fb-46ef-9b84-f6523d4944bd","resolution":{"observed_at":"2026-08-16T10:40:50.541812Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.221487Z","title":"Can deep learning wound segmentation algorithms developed for a dataset be effective for another dataset? A specific focus on diabetic foot ulcers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.221487Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:a51b9d20bcf5e1380b35835b77f2bf0688c7aa1f0777dbe7c484a4eae1a9b129","observation_id":"2d4d8854-a598-46eb-bb85-b8fb096ba8f8","resolution":{"observed_at":"2026-08-16T10:40:50.221487Z","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":"2026-08-16T10:40:50.225833Z","title":"State of the Art on Diffusion Models for Visual Computing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.225833Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:009dc409a5c08c0593d12e75bf0ca47dfb1ce195c33b9bd5fa0c56098d58737f","observation_id":"acc66466-0213-42a2-905e-1a2113631039","resolution":{"observed_at":"2026-08-16T10:40:50.225833Z","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":"10.1002/wics.1629","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.519836Z","title":"A comprehensive review of generative adversarial networks: Fundamentals, applications, and challenges,","venue":null,"work_id":"43439398-ee54-4522-8baf-ce9322d491ea","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.230610Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:eeeaaf5324f086681524f62a146f91a06d304104cd3d3f13a7714a223b4d6f79","observation_id":"53e1a530-720c-4d71-bf9c-f5d6ce2f58d5","resolution":{"observed_at":"2026-08-16T10:40:50.523210Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.234718Z","title":"Recent Advances in Variational Autoencoders with Representation Learning for Biomedical Informatics: A Survey,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.234718Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:ba260a7e20d111b70c9dec48d20828dbc8424ec29c4e9276cedbbfe9b2e43be3","observation_id":"9d4ffc37-a6dc-4f45-a897-7c189afd1c9d","resolution":{"observed_at":"2026-08-16T10:40:50.234718Z","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":"2026-08-16T10:40:51.429023Z","title":"MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model","venue":null,"work_id":"f51dc219-63b3-4b7e-bf99-0ba1809233f2","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.239277Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:0ae65da0386e677627e5b298ecd259bc1fa42e4a8b7779172674c287e026512f","observation_id":"622565aa-8d9e-408c-bc4e-e48eecf3cda9","resolution":{"observed_at":"2026-08-16T10:40:51.433803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.243031Z","title":"Diffusion model-based text-guided enhancement network for medical image segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.243031Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:c2b50c22ea0f17d30d62a62838746a3cfed1d80c7cfa840add2748d39ca48059","observation_id":"897a5408-354c-44f3-af8b-1d120f8c6e4d","resolution":{"observed_at":"2026-08-16T10:40:50.243031Z","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":"10.1007/978-3-030-51935-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.509375Z","title":"Semantic segmentation of diabetic foot ulcer images: Dealing with small dataset in dl approaches,","venue":null,"work_id":"2a229709-8bea-455f-8377-93fcd7c4afd0","year":2020},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.247928Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:6f6f44675c569cbe00213d0cdd9797d7944b3934925f2c9146221c6149ba321c","observation_id":"83b5a6c4-11f4-4579-9c53-7d958a072a25","resolution":{"observed_at":"2026-08-16T10:40:50.512764Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41598-024-80691-w","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.498073Z","title":"A few-shot diabetes foot ulcer image classification method based on deep ResNet and transfer learning,","venue":null,"work_id":"d826ed12-069e-485c-93ae-b65550c0b1c9","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.251815Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:47c26abfbf40ee1d29722e84c98b5e5796f1d3d28c2e7796bedbd807271a5f08","observation_id":"b0198445-0d0b-4093-b262-dddd87aa7038","resolution":{"observed_at":"2026-08-16T10:40:50.501613Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08422","last_updated":"2024-01-16T15:08:38Z","snapshot_observed_at":"2026-08-17T12:57:03.943710Z","submitted_at":"2024-01-16T15:08:38Z","title":"Improving Limited Supervised Foot Ulcer Segmentation Using Cross-Domain Augmentation","version":1},"cited_work":{"arxiv_id":"2401.08422","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.08422","snapshot_observed_at":"2026-08-16T10:40:50.964737Z","title":"Improving Limited Supervised Foot Ulcer Segmentation Using Cross-Domain Augmentation","venue":"cs.CV","work_id":"229aef1e-3b8d-4da4-8028-5bc50ee5a976","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.255641Z"},"links":{"cited_paper":"/paper/2401.08422","citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:10c440457211393f87b161e797266a77cef0f41ff5cf04953daff201bf595610","observation_id":"4e0ff5a8-1dad-4de4-a85f-994e02655267","resolution":{"observed_at":"2026-08-16T10:40:50.969469Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/cisp-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.949552Z","title":"A framework of wound segmentation based on deep convolutional networks,","venue":null,"work_id":"6be6610f-96a0-40b5-a0a8-1509fb26ab33","year":2017},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.260064Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:290ad40931607238bff4dacd8856c2023863a39474b953df0db4b9770b1e365e","observation_id":"f5d36ae4-a877-432b-bdcd-d616b6298614","resolution":{"observed_at":"2026-08-16T10:40:50.953134Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41598-020-78799-w","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.488343Z","title":"Fully automatic wound segmentation with deep convolutional neural networks,","venue":null,"work_id":"ace87ee4-015f-431c-8d9a-0939d0b06cd2","year":2020},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.263641Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:f5ea12308012165a5685ffc059344e7b45b922ea764c9db27331f6304a947a80","observation_id":"57c433d1-7ea8-415f-b82f-52f4e0b8a2e8","resolution":{"observed_at":"2026-08-16T10:40:50.491616Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.267634Z","title":"Automatic Foot Ulcer Segmentation Using an Ensemble of Convolutional Neural Networks,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.267634Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:856acc60995c3b6dc4a9a29799d3f9e3eac3d94ad9155aa0f646be5b67a6904a","observation_id":"8c9be39a-9df2-4ed4-b741-74427cb509a8","resolution":{"observed_at":"2026-08-16T10:40:50.267634Z","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":"2026-08-16T10:40:51.417199Z","title":"Translating Clinical Delineation of Diabetic Foot Ulcers into Machine Interpretable Segmentation,","venue":null,"work_id":"c46ab5d6-33e9-43ef-a95f-ac14560a63a0","year":2022},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.271280Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:b449cd2ceb279bc89f11558b80be9799b192153f6cb95178aae3ff5c4bd7241c","observation_id":"a03a9ceb-dd58-4748-a83a-89fa629b5d5b","resolution":{"observed_at":"2026-08-16T10:40:51.421614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-031-26354-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.478099Z","title":"OCRNet for Diabetic Foot Ulcer Segmentation Combined with Edge Loss,","venue":null,"work_id":"896cc244-506d-421d-aee1-e839eb2259f2","year":2023},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.280325Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:c1679c8b0ed8b6fd9a4b0d8ea276598c1527cb250a9afb31e3898f238fefba7f","observation_id":"b3dac39a-5a88-46cd-b630-d6759649cac5","resolution":{"observed_at":"2026-08-16T10:40:50.481813Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.284991Z","title":"Diabetic Foot Ulcer Segmentation Using Convolutional and Transformer-Based Models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.284991Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:6670596326472e59d189a3c3d63df1292e2f6b2e84cfb759b1031961ed6bede1","observation_id":"edb76ef6-daa5-4742-a69a-4b8ace591845","resolution":{"observed_at":"2026-08-16T10:40:50.284991Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1155/2014/851582","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.459929Z","title":"Automated Tissue Classification Framework for Reproducible Chronic Wound Assessment,","venue":null,"work_id":"a7dce299-f851-42d6-b78e-16dd7b0f0f33","year":2014},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.289542Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:64cb87e3c35a42aaefced33fc17c60361ae0c4328a6bab13cc10de090cb6695a","observation_id":"916085f9-cf56-42da-9911-51878f6ba076","resolution":{"observed_at":"2026-08-16T10:40:50.463740Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.12968/jowc.2022.31.8.710","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.447956Z","title":"Wound tissue segmentation by computerised image analysis of clinical pressure injury photographs: a pilot study,","venue":null,"work_id":"455b89e0-2642-48f5-b618-0e75a1fe2edc","year":2022},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.293659Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:d9ec58015ebbaa1ce378f911667dcbf217e83aa265e5e9c1dc6944fb2b991afe","observation_id":"d14a845d-9673-4c15-a953-c3f9c58ba10b","resolution":{"observed_at":"2026-08-16T10:40:50.451783Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.2196/36977","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.435577Z","title":"Fully Automated Wound Tissue Segmentation Using Deep Learning on Mobile Devices: Cohort Study,","venue":null,"work_id":"035f492d-ca00-4e9e-9d3d-57182bd785a2","year":2022},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.298243Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:0419c5455301c4fc8da7587e237c58e902734335ba45e20c7a5401c9a2965453","observation_id":"83df0f80-5cbf-4d8d-9846-a174a97be76e","resolution":{"observed_at":"2026-08-16T10:40:50.440360Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1049/tje2.12016","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.423856Z","title":"Simultaneous wound border segmentation and tissue classification using a conditional generative adversarial network,","venue":null,"work_id":"0a7ba32a-9eb9-42c0-afb8-0c0fa4a2fcfe","year":2021},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.302605Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:8bbb7cfe0630b45762c1fd57745f14975d2f960e85f47a91ae1779830bf9bece","observation_id":"db32b72a-db4a-49bc-86f3-304e48e08a88","resolution":{"observed_at":"2026-08-16T10:40:50.427661Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.16012","last_updated":"2024-06-23T05:01:51Z","snapshot_observed_at":"2026-08-16T13:40:26.612235Z","submitted_at":"2024-06-23T05:01:51Z","title":"Wound Tissue Segmentation in Diabetic Foot Ulcer Images Using Deep Learning: A Pilot Study","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.16012","snapshot_observed_at":"2026-08-16T10:40:50.307221Z","title":"Wound Tissue Segmentation in Diabetic Foot Ulcer Images Using Deep Learning: A Pilot Study,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.307221Z"},"links":{"cited_paper":"/paper/2406.16012","citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:0a090b2e3e8298cc123e86bdcfe9480bd9a02d91443c6565e0bdb2f78b624986","observation_id":"51dad8f7-4e60-4c63-8aa2-d9909297643e","resolution":{"observed_at":"2026-08-16T10:40:50.307221Z","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":"10.1038/s41598-024-56626-w","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.412588Z","title":"Integrated image and location analysis for wound classification: a deep learning approach,","venue":null,"work_id":"cf8f63f1-8c8d-454f-bd82-701a48b6e314","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.311725Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:5430a71085e551a2be5f9680d4dbbce20941f961ebda81bced5f3fc8765b0b91","observation_id":"63d91547-89dd-4364-b280-5971718e90e6","resolution":{"observed_at":"2026-08-16T10:40:50.416919Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:51.404071Z","title":"Have I been Trained ?","venue":null,"work_id":"b73c66f3-e56d-4e0a-9c3d-b7fe1ab22c71","year":2025},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.315220Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:0baf3adf5fe4fbb7f027752ec3ee1f4143aa017e5a2295c02208c2957d0c1579","observation_id":"b068d475-ec68-4e27-a510-f7e2e7abedf3","resolution":{"observed_at":"2026-08-16T10:40:51.408468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:51.392000Z","title":"High-Resolution Image Synthesis With Latent Diffusion Models,","venue":null,"work_id":"965f1745-176a-4e28-b225-7f932f978505","year":2022},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.319168Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:24ee4bf00aa2cfe09964420f10fc73e14ce9d3d96d5fe7719074e59cf8eecf08","observation_id":"86c1e910-f97c-43e7-8d71-390302ff9054","resolution":{"observed_at":"2026-08-16T10:40:51.396364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:51.381124Z","title":"Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding,","venue":null,"work_id":"628ab253-ade9-4bca-b737-e6786d6ca88f","year":2022},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.322587Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:8507af479204e7510bbeaab15dc9145b32fac1fbaaa5f7ffa58cbcffda1c1d4e","observation_id":"4663b238-7c76-4182-9a9e-f34d7ce06f4d","resolution":{"observed_at":"2026-08-16T10:40:51.384585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:51.368995Z","title":"Denoising Diffusion Probabilistic Models,","venue":null,"work_id":"0ffc8a9a-cf4e-4997-98d9-8000d928d0df","year":2020},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.326000Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:bea0c86de3419e327b131d55c67be4b83978465629670d8049cf72fb5f206e11","observation_id":"69d6c12a-0d84-425e-aa18-212375cdbfe0","resolution":{"observed_at":"2026-08-16T10:40:51.372760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.330008Z","title":"DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.330008Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:a9cb96d5d0af9996e96f05d24c692986977f9011499fec0c675dad822c2b15b4","observation_id":"0f4bb767-7724-4612-955b-c1531c704324","resolution":{"observed_at":"2026-08-16T10:40:50.330008Z","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":"2026-08-16T10:40:51.358163Z","title":"Diffuse Attend and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion,","venue":null,"work_id":"c2ccc417-e271-453d-9c7c-252b8d1667e9","year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.333720Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:aaf9770534ddffc1fa5a1a069e5247643a02e306edc2202bb0531d20b504f82c","observation_id":"6d5a0ae8-9d73-4c91-a739-e16c7c83a5c4","resolution":{"observed_at":"2026-08-16T10:40:51.362044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T10:40:50.337678Z","title":"FUSegNet: A deep convolutional neural network for foot ulcer segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.337678Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:a403941009617bdc69750760d3d30bb4204da7b0538d7b0ea629a84362be4d7a","observation_id":"1b2cd5a6-2258-4ec9-8a2c-194b5caf990d","resolution":{"observed_at":"2026-08-16T10:40:50.337678Z","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":"2026-08-16T10:40:50.340804Z","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.340804Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:935fac05082636606439b93da4f54fe576587eed1a385f9e60ac66cae74d1460","observation_id":"f741c7cd-6d92-48e2-a926-83017b71365d","resolution":{"observed_at":"2026-08-16T10:40:50.340804Z","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":"2026-08-16T10:40:50.344129Z","title":"Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.344129Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:6ee02efa060876be497f34a0d78ff7cdabdedcb15f40b94c32614fb49355d736","observation_id":"bfc3e361-f252-4dda-8029-35d0cee1b645","resolution":{"observed_at":"2026-08-16T10:40:50.344129Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-16T10:40:51.347938Z","title":"SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers,","venue":null,"work_id":"34fa2da9-1069-4625-aaf9-1842387bd8d5","year":2021},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.348112Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:15dff0ee5127fbabe5028089a79f8e82547aa2fe84d267bfd99084c4dc42d8bc","observation_id":"4c8aea77-8ee3-4d6e-a203-c06be98c5e59","resolution":{"observed_at":"2026-08-16T10:40:51.351413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/bios11060165","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.395572Z","title":"Development of a Smartphone-Based Optical Device to Measure Hemoglobin Concentration Changes for Remote Monitoring of Wounds,","venue":null,"work_id":"af1ad337-629d-4eb0-9af5-8ea870e1dd42","year":2021},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.355879Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:f1ddec988c9b3b10f9996576ae94c70af71ba95cfba0665d79e8353530d86368","observation_id":"3e0ad762-85fb-4679-8453-3b4d94e78ccd","resolution":{"observed_at":"2026-08-16T10:40:50.399482Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.15203","last_updated":"2021-10-28T09:29:17Z","snapshot_observed_at":"2026-08-16T18:20:46.795235Z","submitted_at":"2021-05-31T17:59:51Z","title":"SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.15203","snapshot_observed_at":"2026-08-16T10:40:50.351806Z","title":"Available: https://arxiv.org/abs/2105.15203v3","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.351806Z"},"links":{"cited_paper":"/paper/2105.15203","citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:8cbab9fe252060a3ff209e1b8de1e30f1d2d5c13c5f9314d72f45c016cb9f233","observation_id":"dea4e44a-de46-496a-9f77-161f30e9e715","resolution":{"observed_at":"2026-08-16T10:40:50.351806Z","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":"10.3390/mi10030180","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:40:50.382614Z","title":"Development and Validation of a Smartphone-Based Near-Infrared Optical Imaging Device to Measure Physiological Changes In-Vivo,","venue":null,"work_id":"bc7a5d33-b345-4c8f-a82b-d0ce7751dd93","year":2019},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.360290Z"},"links":{"citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:82fa847c2e7a1aaf74cbecf480e9c0964f1c1a0be5e3c24a0f82c9f186b4e294","observation_id":"5068fb7b-42ae-40c1-8cdc-6d53dbfb75fe","resolution":{"observed_at":"2026-08-16T10:40:50.388671Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.11618","last_updated":"2022-10-03T13:34:41Z","snapshot_observed_at":"2026-08-16T17:05:18.339489Z","submitted_at":"2022-04-22T09:54:35Z","title":"Translating Clinical Delineation of Diabetic Foot Ulcers into Machine Interpretable Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.11618","snapshot_observed_at":"2026-08-16T10:40:50.275541Z","title":"Available: https://arxiv.org/abs/2204.11618v2","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-16T10:40:50.275541Z"},"links":{"cited_paper":"/paper/2204.11618","citing_paper":"/paper/2504.17628"},"observation_digest":"sha256:8dc6e4e64f8f87addc249e304e96b0fae7e8e8d51d02157bd26b808a2037f68b","observation_id":"32f36dd3-e0ea-4752-8df9-3489cb9f4267","resolution":{"observed_at":"2026-08-16T10:40:50.275541Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2504.17628","last_updated":"2025-04-24T14:50:10Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-17T00:27:04.847581Z","submitted_at":"2025-04-24T14:50:10Z","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization"},"reference_resolution":{"displayed":50,"state_counts":{"malformed_identifier":8,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":19,"verified_fuzzy":8},"total_outbound_references":50},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2504.17628."}