{"as_of":"2026-08-08T23:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e4f0b0fc12c35926050ce26017bfc4f48671371b4a414a10ad8f761d211857a8","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:48:14.182550Z","state":"measured"},{"denominator":37,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":37,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2506.17232/citation-record","integrity":"/paper/2506.17232/integrity","json":"/paper/2506.17232/citation-record.json","paper":"/paper/2506.17232"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:20.456137Z","title":"Self- supervised representation learning for geospatial objects: A survey.Informa- tion Fusion, page 103265, 2025","venue":null,"work_id":"64cd5506-73ee-454a-b645-b495beecdfa8","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.253802Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:b56f19412e9c3206171b141e3ed5947be27a648724cbf5017864f495894b9c72","observation_id":"eb37fe32-7302-4a26-be34-53d28886d55d","resolution":{"observed_at":"2026-08-07T13:48:20.531928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:20.305885Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":"23cc188c-a2ce-445c-bc8b-2180eae00b27","year":2020},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.396304Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:fc4b8b96458f1b16d07cef1d6d006c55aa7694678f6df30456fb2bd282b5b3c2","observation_id":"b2ad9cb6-a4d6-40ea-8dc5-d0016038ebd7","resolution":{"observed_at":"2026-08-07T13:48:20.373847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:20.043093Z","title":"Cross-domain gradi- ent discrepancy minimization for unsupervised domain adaptation","venue":null,"work_id":"98585120-7116-4ad1-b51e-e2837ef43a97","year":2021},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.476885Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:9251fc8cee4e66c3f78c1a859e414b18b2999987f10cc671786c1f36acc0d137","observation_id":"3469fddd-f513-471b-9e82-7c6c7fd0123c","resolution":{"observed_at":"2026-08-07T13:48:20.161052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:19.857877Z","title":"Learning to detect open classes for universal domain adap- tation","venue":null,"work_id":"3ccfae8c-6283-4c80-9646-ed40814599ce","year":2020},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.548501Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:ee1f39a92efa6815be30a0a34d34593d08ca943689ade3ec7f94d7e5e7dd0eaa","observation_id":"722be3dd-a857-4a7d-8e1c-f30846bba378","resolution":{"observed_at":"2026-08-07T13:48:19.979994Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:19.623076Z","title":"Mic: Masked image consistency for context-enhanced domain adaptation","venue":null,"work_id":"beb478af-044e-4b5b-9a25-6d6258c6fa9c","year":2023},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.638572Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:7b8974127aedb144915ea05f08f50253a850d9e1827306725ec66850655451b2","observation_id":"d4a5eff2-e0ff-44fb-8804-0c8ff47039a9","resolution":{"observed_at":"2026-08-07T13:48:19.752662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:19.341505Z","title":"Multi- source domain adaptation for panoramic semantic segmentation.Information Fusion, 117:102909, 2025","venue":null,"work_id":"542661b1-480a-4daa-a721-9b90543a1a83","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.731587Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:7c356413399ae0e823d19cdac22252d39ebc65bfd22021e0ccd955067e7dc284","observation_id":"c4210247-bb35-4721-a577-0a67c63640b1","resolution":{"observed_at":"2026-08-07T13:48:19.468147Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:19.107382Z","title":"Patch-mix transformer for unsupervised domain adaptation: A game perspective","venue":null,"work_id":"d38b89de-562a-4240-b560-650b7838a3ca","year":2023},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.823546Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:0d4f7561b44d3c564a83a3512d078acab5056058eba7c1fbce66ad04ad6f8e20","observation_id":"55984c79-7067-46b7-8a86-3e100dfc47fa","resolution":{"observed_at":"2026-08-07T13:48:19.224620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:18.906037Z","title":"Crossfuse: A novel cross attention mechanism based infrared and visible image fusion approach.Information Fusion, 103:102147, 2024","venue":null,"work_id":"776a7bf7-0c8c-46bf-96ca-6c2911dde902","year":2024},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:11.936561Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:e54310af692d227e3f362a6a9d53f580472f53e87ff98dc1982b0b8225fadc6f","observation_id":"0de40bf5-4b27-4939-a9fc-bcd8fca4df05","resolution":{"observed_at":"2026-08-07T13:48:18.992995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:18.742228Z","title":"Cross-domain adaptive clustering for semi-supervised domain adaptation","venue":null,"work_id":"d4739017-1ddc-4a32-b7ea-c2baa44a6096","year":2021},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.036042Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:16559437d8a2d1d65cb9f8867e604fc13506f4609ce5ebb88101c55294f9c7ef","observation_id":"e61c108a-3cca-4a90-84cd-928fbd09a047","resolution":{"observed_at":"2026-08-07T13:48:18.820480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:18.588637Z","title":"Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation","venue":null,"work_id":"147b79f3-3107-48f7-ab1c-b3f0de7da7cf","year":2020},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.127770Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:fe1e519b3030af7c80960fdb0862e9db9b88f4536f8ddc0fbef49b851c39aa05","observation_id":"8beb98ae-1463-402d-b98d-6ea509cd9eda","resolution":{"observed_at":"2026-08-07T13:48:18.681704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:18.448195Z","title":"Foregroundguidanceandmulti- layer feature fusion for unsupervised object discovery with transformers","venue":null,"work_id":"6d51edd1-2fe3-42b9-a9fc-5e7fef49fb56","year":2023},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.249948Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:717564508d7c641fc0516bd3eaf84a6fd9c78a36eb05d83b705a5c1c2f7ef87a","observation_id":"5d52357b-6e97-4c06-ba99-7c223487bfc2","resolution":{"observed_at":"2026-08-07T13:48:18.478684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:18.223967Z","title":"F2net: Learning to focus on the foreground for unsupervised video object segmentation.AAAI, 35(3):2109–2117, 2021","venue":null,"work_id":"a26948ee-e6dc-4643-ad42-09ff66ca5c72","year":2021},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.391888Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:e4d2ce03b45e92407fbec39e16411b034b30b4980a4221b434e2bf79137752de","observation_id":"7ec3aebc-f7dd-44bb-9a29-04327cc6249d","resolution":{"observed_at":"2026-08-07T13:48:18.327105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:17.980860Z","title":"Explicitly fusing plug-and-play guidance of source prototype into target sub- space for domain adaptation.Information Fusion, 123:103197, 2025","venue":null,"work_id":"80805009-5e06-4427-b146-84d4d26b0d81","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.499876Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:619cf6b475854ee07bd2694016ca6ab18e705c78e3d8cf47bb34b0bb9418b3bd","observation_id":"8434ee43-ca14-495a-817f-52b35ce642af","resolution":{"observed_at":"2026-08-07T13:48:18.107109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:17.787263Z","title":"Explicitly fusing plug-and-play guidance of source prototype into target sub- space for domain adaptation.Information Fusion, page 103197, 2025","venue":null,"work_id":"ca2a55e6-0418-4b6f-864b-0a5da2ff1f7a","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.641757Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:ed4a6a6841aefc7d1febf5a49f8ed7084a38c16046e927aebf5f13d8778d5f5f","observation_id":"42c6796f-38db-477d-b2de-df11db4763b3","resolution":{"observed_at":"2026-08-07T13:48:17.887091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:17.673445Z","title":"Making the best of both worlds: A domain-oriented transformer for unsupervised domain adaptation","venue":null,"work_id":"4159d30e-8c0d-4f81-9b75-100a3ab4b44e","year":2022},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.728009Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:9030f556eb3ef8ccc68d1358e3c7e937ab9a7c15831afc4a6fbb42d9b624d38f","observation_id":"5badc355-99e4-42b4-b173-9fcaa32a8253","resolution":{"observed_at":"2026-08-07T13:48:17.713500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:17.448594Z","title":"Fixbi: Bridging domain spaces for unsupervised domain adaptation","venue":null,"work_id":"e1f738b7-ad34-466a-a5ff-22c7970fd369","year":2021},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.858508Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:94d619a7e4c2c45ec69a6dcb1c247e6859a924c5cd1532b37aeea6848eda9a99","observation_id":"74899426-188b-443e-90f3-7af5da237ac3","resolution":{"observed_at":"2026-08-07T13:48:17.568409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:17.203504Z","title":"Moment matching for multi-source domain adaptation.Int","venue":null,"work_id":"234de3b5-dc96-43bd-a83e-085e67b68897","year":2019},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.912102Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:8a209ca38aaf0124d7e3f9500bf6c043508b463efddc24395d433b05ed769d21","observation_id":"e15e644c-ff87-4f35-bd74-e8d12d8e499f","resolution":{"observed_at":"2026-08-07T13:48:17.299474Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.06924","last_updated":"2017-11-29T04:04:18Z","snapshot_observed_at":"2026-08-07T12:49:34.214845Z","submitted_at":"2017-10-18T20:20:49Z","title":"VisDA: The Visual Domain Adaptation Challenge","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.06924","snapshot_observed_at":"2026-08-07T13:48:12.968641Z","title":"Visda: The visual domain adaptation challenge.arXiv preprint arXiv:1710.06924, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:12.968641Z"},"links":{"cited_paper":"/paper/1710.06924","citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:bc0b854e5975faf65deea94cb97f28bef68186dffa25a5cb43c92372a0b7e7a9","observation_id":"2471db44-e955-45e1-a54a-eae4cc6cbf3b","resolution":{"observed_at":"2026-08-07T13:48:12.968641Z","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":"2026-08-07T13:48:17.032425Z","title":"Domain-specificity inducing transformers for source-free domain adaptation","venue":null,"work_id":"80665ff7-b548-43c6-90e5-9c9fb7e7b1d5","year":2023},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.055658Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:4b4020ad8cecbe1f36d893821823fc89d4e67bcaf6a84df11c034709fe8f0012","observation_id":"b099c67f-313c-4603-9e9f-d3c8156e23f1","resolution":{"observed_at":"2026-08-07T13:48:17.098439Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:16.837750Z","title":"Aligning non-causal factors for transformer-based source- free domain adaptation","venue":null,"work_id":"862d9123-72db-4a0a-b9ca-7718d4b0dafa","year":2024},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.114964Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:95aa6e9428fd4840ec4f87c5ad080a89f31cc1e866addbc8daff570556a9dbfb","observation_id":"b72827f9-3efd-480e-be85-faf75bc570ae","resolution":{"observed_at":"2026-08-07T13:48:16.911595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.12176","last_updated":"2021-01-28T18:32:14Z","snapshot_observed_at":"2026-08-04T15:33:31.839842Z","submitted_at":"2021-01-28T18:32:14Z","title":"On the Origin of Implicit Regularization in Stochastic Gradient Descent","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.12176","snapshot_observed_at":"2026-08-07T13:48:13.191636Z","title":"On the origin of implicit regularization in stochastic gradient descent.arXiv preprint arXiv:2101.12176, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.191636Z"},"links":{"cited_paper":"/paper/2101.12176","citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:9ddcaa9556285be368c3581fb6349889ecb1b84a2e30f284f3eddadca2245b3e","observation_id":"e052d641-3d40-4dbb-a5fd-ce1b4374dae9","resolution":{"observed_at":"2026-08-07T13:48:13.191636Z","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":"2026-08-07T13:48:16.603959Z","title":"Training data-efficient image transformers & distillation through attention","venue":null,"work_id":"cf0cc020-84c2-4e4f-a429-323332999674","year":2021},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.231356Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:477210d05cfb6c15f1f766ba025767e96d7c839da88e6e1874317e81c35aadd2","observation_id":"5ca33106-2ef3-4fb7-b1f8-2bd7d867cf3e","resolution":{"observed_at":"2026-08-07T13:48:16.724221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:16.386984Z","title":"Zico Kolter, Louis- Philippe Morency, and Ruslan Salakhutdinov","venue":null,"work_id":"85e44728-40ed-4a76-84c5-d6aec4abf7fa","year":2019},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.305643Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:738cfdbdc583ab68d4a862c84535c8da08a00767835e190a0f50216f6bebd91d","observation_id":"51c3c8d5-7172-49c5-8f37-873ffa7d65c3","resolution":{"observed_at":"2026-08-07T13:48:16.494098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:16.196441Z","title":"Deep hashing network for unsupervised domain adaptation","venue":null,"work_id":"ece496b5-769b-4035-a291-8674e4bbba03","year":2017},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.390904Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:a279ee445b5242e9a7527a67098c179187697bbce2797a038fc6a30987832c36","observation_id":"35e5b389-9c89-44a6-b7e7-d80f303f2b5f","resolution":{"observed_at":"2026-08-07T13:48:16.252581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:16.069849Z","title":"Nwpu-crowd: A large-scale benchmark for crowd counting and localization.TPAMI, 43(6):2141–2149, 2020","venue":null,"work_id":"54337fc4-af7b-4366-b691-b0671ae330fc","year":2020},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.458547Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:2e8b2ec68400d60de9fe6484a1383c0125400e4ca13e24cc27bfa2a60086453b","observation_id":"03028012-6856-46f9-98bb-6c0d16029de5","resolution":{"observed_at":"2026-08-07T13:48:16.132157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:15.945488Z","title":"Multidimensional fusion of frequency and spatial domain information for enhanced camouflaged object detection.Information Fusion, 117:102871, 2025","venue":null,"work_id":"5da441a9-8c10-4caf-9a51-ed7469f58b4f","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.515503Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:5a2f7aa304fea37344007f24ca9d2072f74a1244bedb0885433ba82b5805f9bc","observation_id":"90a219e8-638e-4c98-b9d9-0f38a45ef816","resolution":{"observed_at":"2026-08-07T13:48:16.008847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:15.821434Z","title":"Multi-teacher self-distillation based on adaptive weighting and activation pattern for enhancing lightweight arrhythmia recognition.Information Fusion, 122:103178, 2025","venue":null,"work_id":"33ab8a7b-8923-4169-b12a-93f3a7b08ba9","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.577169Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:8296b9b4b27f0ba63fba729ef842c041354f9533b447f20a134e9bfc64264ca7","observation_id":"d79595fc-f7f7-4320-a9c1-a8542df3d714","resolution":{"observed_at":"2026-08-07T13:48:15.864860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:15.708042Z","title":"Aid: A benchmark data set for perfor- mance evaluation of aerial scene classification.TGRS, 55(7):3965–3981, 2017","venue":null,"work_id":"d4f397b2-d177-4b92-9bab-37a4a8990e25","year":2017},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.633460Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:9b615890ee02e953e23d4d6365fbfa7f139ab0bf5fbb88b52306dcbe5d33e22c","observation_id":"89fc6056-7b28-4eeb-a67d-1ae3474dd4c2","resolution":{"observed_at":"2026-08-07T13:48:15.747246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:15.543909Z","title":"Universal domain adaptation for remote sensing image scene classification.TGRS, 61, 2023","venue":null,"work_id":"91161aa3-4a1a-4bac-b25e-7fc288a396b0","year":2023},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.684004Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:bd3e0096aaf044e7c6f04f8a30a2a8fc17aea965daab9155609220c93a838825","observation_id":"f6da2053-e269-44c1-b6b7-344cb4b5c404","resolution":{"observed_at":"2026-08-07T13:48:15.621173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:15.386009Z","title":"Cdtrans: Cross-domain transformer for unsupervised domain adaptation","venue":null,"work_id":"c5acfc12-18f3-4833-ab1e-def920331ff7","year":2022},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.768492Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:0be54c5158d074c9fdf6ed165598b99192ac116cd3ec4366b7f5f1c1a8962df2","observation_id":"8ac235c6-36dd-42f0-854c-4b2270f91c64","resolution":{"observed_at":"2026-08-07T13:48:15.451663Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:15.199864Z","title":"Ccin-sa: Composite cross modal interaction network with attention enhancement for multimodal sentiment analysis.Information Fusion, page 103230, 2025","venue":null,"work_id":"ec440efd-1929-48af-a55f-cb867cda6efe","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.840696Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:8cfcb889298030638262ca3c6e25cb2530c96de221acff11b528ba1502e031ea","observation_id":"f7520674-bc4f-4cc5-a0ac-0ee841b1ae37","resolution":{"observed_at":"2026-08-07T13:48:15.304765Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:15.034563Z","title":"Pseudo-margin-based universal domain adaptation","venue":null,"work_id":"0acef757-9d56-4071-b936-0a8b46b8b784","year":2021},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.915061Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:e652b8bf8143d1bb6e842938c3c6542ca4031d92bd9062d1fb2ec5e1d168050f","observation_id":"96272c9a-12b5-4dbc-9b95-63c2781c2742","resolution":{"observed_at":"2026-08-07T13:48:15.099540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:14.880666Z","title":"Universal domain adaptation","venue":null,"work_id":"3e98654e-0930-46d4-991a-0bca68be4a0c","year":2019},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:13.982828Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:fb59b5bea338cf470987a6cd65b081a9526691247f7983b50748a46bf8fce78b","observation_id":"9eb7deaa-103d-4496-8518-e8cdb94fe0df","resolution":{"observed_at":"2026-08-07T13:48:14.954869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:14.751415Z","title":"Dlme: Deep local-flatness manifold embedding","venue":null,"work_id":"6e720e0f-2873-4009-bebc-2489670f6d85","year":2022},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:14.036692Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:873b217373f29ae2f37b2d3ea1a093465ea6d39ce92d4ed7bd652c4276ec1c47","observation_id":"0a2095f3-57f9-4851-980e-1d7d55b9a0a4","resolution":{"observed_at":"2026-08-07T13:48:14.822668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:14.587081Z","title":null,"venue":null,"work_id":"3d2508f5-aa3e-474c-bb92-065955f37fa6","year":2023},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:14.083519Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:a1f1f60e120f711fce938e8edd45122b28b5077766dabb1078b459a2503e1ef4","observation_id":"c7e06666-6f2e-4825-878c-346220fc6ae3","resolution":{"observed_at":"2026-08-07T13:48:14.653020Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:14.447942Z","title":"Free lunch for domain adversarial training: En- vironment label smoothing","venue":null,"work_id":"efc18813-cf58-438c-bb30-34a9021daa7b","year":2023},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:14.124308Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:d079900e6bdac57c215c8a75e9c4b6e6d5affb4414c240b18ae8d41818e6ef9f","observation_id":"5c22a12a-8ee4-4c9e-880a-066d1807e933","resolution":{"observed_at":"2026-08-07T13:48:14.486491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:48:14.317956Z","title":"Multi- sourcemulti-modaldomainadaptation.Information Fusion, 117:102862, 2025","venue":null,"work_id":"92368d9d-7f0c-4b0e-8f57-b5b2128c924a","year":2025},"citing_paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T13:48:14.182550Z"},"links":{"citing_paper":"/paper/2506.17232"},"observation_digest":"sha256:4748057518e0db9f6c6b9a994b2d712f9b42ed935e05266d75103cee186ff3e1","observation_id":"ccf6b0c5-c565-4e43-867b-5f14cc0dd062","resolution":{"observed_at":"2026-08-07T13:48:14.373791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.17232","last_updated":"2025-05-27T09:48:29Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T13:40:49.500430Z","submitted_at":"2025-05-27T09:48:29Z","title":"PCaM: A Progressive Focus Attention-Based Information Fusion Method for Improving Vision Transformer Domain Adaptation"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":34},"total_outbound_references":37},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2506.17232."}