{"as_of":"2026-08-23T17:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:195957b08c35aa38016c404ac477af56c57460162405f7cb4ab7489a3b1cf5b6","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T05:53:45.772547Z","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":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T17:51:27.722427Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-15T17:51:27.806339Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"cited_work":{"arxiv_id":"2504.19598","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.19598","snapshot_observed_at":"2026-08-15T17:51:27.806339Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","venue":"cs.CV","work_id":"10ae0aff-01cc-4482-8bd5-c54caa2029a9","year":2025},"citing_paper":{"arxiv_id":"2507.20259","last_updated":"2025-07-27T13:06:32Z","snapshot_observed_at":"2026-08-15T17:44:21.969284Z","submitted_at":"2025-07-27T13:06:32Z","title":"L-MCAT: Unpaired Multimodal Transformer with Contrastive Attention for Label-Efficient Satellite Image Classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T17:51:27.722427Z"},"links":{"cited_paper":"/paper/2504.19598","citing_paper":"/paper/2507.20259"},"observation_digest":"sha256:06b066d2df8d8a0df00a9d68d41cdb38691adfbeaae86e1785b729c75d3ea9b5","observation_id":"6d8efd71-8e76-41d0-a5bd-6bd7c9b7aa20","resolution":{"observed_at":"2026-08-15T17:51:27.811509Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2504.19598/citation-record","integrity":"/paper/2504.19598/integrity","json":"/paper/2504.19598/citation-record.json","paper":"/paper/2504.19598"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:53:47.145621Z","title":"A transformer-based siamese network for change detection","venue":null,"work_id":"af38cf87-dce6-42e5-bc7c-b370d51dd9f1","year":2022},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.052862Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:b60a2ccafc8bb2418d162d73a5e3d9756002fbc28582922ecfc252775f28a562","observation_id":"2ad3172f-3040-4265-8715-6a9651fdbe72","resolution":{"observed_at":"2026-08-16T05:53:47.150610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:47.128976Z","title":"Automatic analysis of the difference image for unsupervised change detection","venue":null,"work_id":"0c3fb76a-0763-449d-859a-97af1bff00c0","year":2000},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.097825Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:058568985866a0a4257868a56709f8a797fb6fb76cd5d5659702a1ab96a0763a","observation_id":"323519ab-95c1-4fc5-ba1e-54bca651c697","resolution":{"observed_at":"2026-08-16T05:53:47.134375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:47.114247Z","title":"Unsupervised change detection in satellite im- ages using principal component analysis and k-means clus- tering","venue":null,"work_id":"26984df8-74ba-454a-a334-03e1685d6e3d","year":2009},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.144922Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:6842854a36b0aa5e45a1268d0515b85c46be999b71c6ebb214d717faa9e0f5b0","observation_id":"2ddc83e1-bda4-4329-892b-abb1aaa1f52b","resolution":{"observed_at":"2026-08-16T05:53:47.119087Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:47.099831Z","title":"A spatial-temporal attention- based method and a new dataset for remote sensing image change detection","venue":null,"work_id":"fc522fa5-fc24-4d4b-8f43-8102023a7c2e","year":2020},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.188533Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:bc6d8b9196341df2d788344aede4e508cf5c6a2ad6d28a01d15ab4dc866c5bd3","observation_id":"6488ac26-6b48-4cd6-95bd-58f51957afeb","resolution":{"observed_at":"2026-08-16T05:53:47.104942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:47.085594Z","title":"Remote sensing im- age change detection with transformers","venue":null,"work_id":"3bb1c13d-ce5a-40ee-8ae0-abb031907263","year":2021},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.194071Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:6dc1d4aefecafdb8eacd0fbe76f4d7da986c73d756aecbaa0e1cb6d404c09c65","observation_id":"f073ee89-0f4c-4eb4-b3b9-1e94b96716d2","resolution":{"observed_at":"2026-08-16T05:53:47.090263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:47.070717Z","title":"Dasnet: Dual attentive fully convolutional siamese networks for change detection in high-resolution satellite images","venue":null,"work_id":"1499f9de-687d-488d-a1f2-b244dbef99cf","year":2020},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.199365Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:c6090a62906bbade3d4351e6b6a4dcf16d637a2390777543a3673953bee022fb","observation_id":"6e4131b2-6e98-466e-b028-9455cc71dc3a","resolution":{"observed_at":"2026-08-16T05:53:47.075615Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:47.027671Z","title":"Fccdn: Feature constraint net- work for vhr image change detection.ISPRS Journal of Pho- togrammetry and Remote Sensing, 187:101–119, 2022","venue":null,"work_id":"40008f4e-3840-4732-8a71-8163bfb5da5b","year":2022},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.204419Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:0baf8290ab1926d8272d3c974365f5f5848210220c667a50fc694e7724f5b63f","observation_id":"a3995047-a48b-48d5-8e93-9c8bfd74530f","resolution":{"observed_at":"2026-08-16T05:53:47.048445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.955968Z","title":"A tm tasseled cap equivalent transformation for reflectance factor data","venue":null,"work_id":"4c7c3088-fadc-4626-a1c2-ec898fca5133","year":1985},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.208980Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:cd1f06795c4de198978645d892a7df24d6d408838de95fcbb61f81966ed59436","observation_id":"3297c84f-8b7d-4782-a1ad-5e0b4ba7e925","resolution":{"observed_at":"2026-08-16T05:53:46.998148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.927986Z","title":"Fully convolutional siamese networks for change detection","venue":null,"work_id":"08bcd1dc-5094-49b8-81ec-ae75914811b3","year":2018},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.213512Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:ba365674fe04083743099ca715951ebb2f6155b4d4885f937875ba2a23ad31c9","observation_id":"895a272f-0c93-43ab-b7c9-128e321f3425","resolution":{"observed_at":"2026-08-16T05:53:46.932714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-16T09:25:53.087782Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-16T05:53:45.218020Z","title":"An image is worth 16x16 words: Trans- formers for image recognition at scale","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.218020Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:0e7b6f197e4c531e9271a02848b5ae3bda7117cf9a4e56448993abb990b3b5cb","observation_id":"8d8c93d1-70fb-4a47-8a87-eefdaba1ab4d","resolution":{"observed_at":"2026-08-16T05:53:45.218020Z","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":"2026-08-16T05:53:46.910877Z","title":"Snunet-cd: A densely connected siamese network for change detection of vhr images","venue":null,"work_id":"c925d467-90a8-4ec2-ace7-f7d4124c5b9d","year":2021},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.223196Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:33934f80053f4116583737e99c57e39d47fe72466237d271255164fd4dfdd149","observation_id":"799a756e-4c9e-4644-98cd-cd40fc6ddbd9","resolution":{"observed_at":"2026-08-16T05:53:46.916966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.894321Z","title":"Changer: Feature inter- action is what you need for change detection","venue":null,"work_id":"653d7b90-13fe-487e-9298-4109dc945613","year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.228186Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:dcb55627de2760edecd7bc20cd523faa672e26aa9902e25705902e053c12ecf8","observation_id":"a0f0a5ee-bff4-4bdc-bc80-2dfb7475efbe","resolution":{"observed_at":"2026-08-16T05:53:46.899105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.878838Z","title":"Change detection on remote sensing images using dual- branch multilevel intertemporal network","venue":null,"work_id":"64259957-fcdc-4436-9ab8-b8c5a67c0fa9","year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.232929Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:cdc7a95dc764cc7fa45da08ce2f9548762d52d5d9bb6902413fb80f78c2e9b9d","observation_id":"b6d42881-5480-4846-a934-d80e5ecfcda0","resolution":{"observed_at":"2026-08-16T05:53:46.883970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.863417Z","title":"Change detection in synthetic aperture radar images based on deep neural networks.IEEE transactions on neural networks and learning systems, 27(1):125–138, 2015","venue":null,"work_id":"50d63b07-8cc2-467f-a0ed-059dda0d1742","year":2015},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.237707Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:e53c6467ff383d1bf3008d645c1ae8fc7a3ac1ca7219450231611b3261f3bd3d","observation_id":"ad6c15ca-fcdf-4b86-bdd8-f0f0ecbbbc43","resolution":{"observed_at":"2026-08-16T05:53:46.868420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.848353Z","title":"Deep residual learning for image recognition, 2015","venue":null,"work_id":"3e7dcc00-1f9e-4a03-b89c-734be43eb18d","year":2015},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.242917Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:b8ad7446b43f1046085609d7a9e63dc0789800b721792a1fc40d627bcce7a5a5","observation_id":"11e908ae-c109-47af-a18e-7f4c279878b8","resolution":{"observed_at":"2026-08-16T05:53:46.853014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.833724Z","title":"Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco An- dreetto, and Hartwig Adam","venue":null,"work_id":"a2aa33a0-a0f0-4ba1-9a33-1872627c56c7","year":2017},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.247280Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:4e0afb1d6f60bce0c1613399a39ac22f438caf812b48a183589a8e38e24c34f4","observation_id":"16b3fd3a-0fdf-4456-b69d-93c0c66f67ef","resolution":{"observed_at":"2026-08-16T05:53:46.838408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.251933Z","title":"Squeeze-and-excitation net- works","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.251933Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:6191ba8b39a631744a852427f01945817af8bf4530fee057bd986dbee46d0150","observation_id":"82182178-107f-4ed5-9e29-1bfd254cd732","resolution":{"observed_at":"2026-08-16T05:53:45.251933Z","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":"2026-08-16T05:53:46.807245Z","title":"Spatiotemporal enhancement and interlevel fusion net- work for remote sensing images change detection","venue":null,"work_id":"f1a75462-254e-453a-aa95-33cbaeba0952","year":2024},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.256808Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:281447ef2101a27b576d33383adc7a0dc9b6aa5703b7e14ce6724f6f5b31451d","observation_id":"f5aef187-c6d4-4d86-a5d6-71f92bc46383","resolution":{"observed_at":"2026-08-16T05:53:46.813326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.597553Z","title":"Batch normalization: Accelerating deep network training by reducing internal co- variate shift","venue":null,"work_id":"9a3ed49a-2048-4382-ae76-bb372617d124","year":2015},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.261831Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:9ecbd98c832d16f8a8133f4f4129fbe3643dbfed8508cac5f6cb6191960e0dad","observation_id":"c8996db0-5dd4-4862-a587-298f1bbb1584","resolution":{"observed_at":"2026-08-16T05:53:46.711870Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.266853Z","title":"Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.266853Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:a4c4393042023bcc49ed027b7563c1a6d9fcefa0eab1a6d7329b6b98481db2cc","observation_id":"6350d10a-028e-4b8b-8734-ac8b4231c461","resolution":{"observed_at":"2026-08-16T05:53:45.266853Z","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":"2026-08-16T05:53:46.537213Z","title":"Deep learning for change detection in remote sensing images: Comprehensive review and meta-analysis","venue":null,"work_id":"f3196a1a-27d4-4369-ac68-592a3465fc82","year":2020},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.271696Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:20e421a771ae8bbb27ec237abab1265e8fdb2fcfa1b14b83ac61e248ec61dee2","observation_id":"3ac917ea-0a51-4648-a0d7-e1a7c64b30e9","resolution":{"observed_at":"2026-08-16T05:53:46.546860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.276522Z","title":"Segment any- thing","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.276522Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:f9146a43d76eb9f5ccfdc13be1cef92c7cf0995fa0750cb4cbb8d74a31597984","observation_id":"ac5b36c6-f977-4f26-8291-cb3f8360daf1","resolution":{"observed_at":"2026-08-16T05:53:45.276522Z","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":"2026-08-16T05:53:46.510455Z","title":"Change detection in remote sensing images using conditional adversarial networks","venue":null,"work_id":"e5f021ee-6635-46f2-9bcd-8f1f54925815","year":2018},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.281042Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:9ebbea9800f1f7bbcb592dde816f7109392eb8a2d28df20d2402904933b12e19","observation_id":"da218520-a4bf-4d03-b58b-3a9af9927c3e","resolution":{"observed_at":"2026-08-16T05:53:46.515761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.495874Z","title":"A new learn- ing paradigm for foundation model-based remote sensing change detection, 2023","venue":null,"work_id":"3b6f3308-5f98-4408-83e6-e45e0236d32a","year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.285811Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:ac474e7c4150bf4c6f7d2908066e78189a4959087c8fcd83b41515bf368191b2","observation_id":"b4987726-2b12-4968-817b-09bef8a14646","resolution":{"observed_at":"2026-08-16T05:53:46.500341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.480562Z","title":"A new learn- ing paradigm for foundation model-based remote-sensing change detection","venue":null,"work_id":"59673a87-0903-48d4-b07f-08a7bfd07897","year":2024},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.290315Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:75db95f640b78fb7c9f3a92881be205c25004e057cd14ff582edee5c69b1afb4","observation_id":"649ef6a1-7ff0-42eb-adf4-b3f771bc823d","resolution":{"observed_at":"2026-08-16T05:53:46.485551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.464637Z","title":"Tran- sunetcd: A hybrid transformer network for change detec- tion in optical remote-sensing images","venue":null,"work_id":"0d2207ee-322f-4199-8ff4-4425f6e75f70","year":2022},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.295128Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:79027a723c8ab28bc47b6b51671f33f60532c9ba0357de83a6158a183b479ee4","observation_id":"c642e784-c897-46eb-911b-db9625dd545c","resolution":{"observed_at":"2026-08-16T05:53:46.469874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.448894Z","title":"A densely attentive refinement network for change detection based on very-high-resolution bitemporal remote sensing im- ages","venue":null,"work_id":"a7517985-0be5-4de1-91ca-7672524604e0","year":2022},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.299313Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:23344daa750d4c94bc672c95721b22c25f68873477973ddc6dfde2658c721647","observation_id":"96673784-3b8b-41bd-919c-18fd522de655","resolution":{"observed_at":"2026-08-16T05:53:46.454245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.330473Z","title":"Re- moteclip: A vision language foundation model for remote sensing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.330473Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:5d47a85d8eb15b4c6e180937c610cf597a8af9634b7926cfa00412e20eaa9fdd","observation_id":"96d1bfa9-a424-496f-9531-7eb18345909a","resolution":{"observed_at":"2026-08-16T05:53:45.330473Z","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":"2026-08-16T05:53:46.422607Z","title":"Smnet: symmetric multi-task network for semantic change detection in remote sensing images based on cnn and transformer","venue":null,"work_id":"8e202c20-a260-4396-8ce1-3eae51fc4f19","year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.367374Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:ced55a163c4a459f3d29a57a365f1b36ed565054d4d2d5c1431f14ef7708c90d","observation_id":"ee0dae15-5023-4ccf-a069-3fc28f4b3d3b","resolution":{"observed_at":"2026-08-16T05:53:46.428131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.304166Z","title":"Two at once: Enhancing learning and generalization capacities via ibn-net, 2020","venue":null,"work_id":"6bb6b843-b7f2-426e-829e-37c1c18d603d","year":2020},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.404855Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:1286e7a54c63e8c9dee17b71ca1ba4ec1d0b4e30108f2b693a1137b4c9378f0d","observation_id":"65b2525d-3e35-430a-be2a-1461bfc68f5c","resolution":{"observed_at":"2026-08-16T05:53:46.374011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.151867Z","title":"End-to- end change detection for high resolution satellite images us- ing improved unet++","venue":null,"work_id":"fad67f24-9776-4edc-8d0b-138615578c2e","year":2019},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.438170Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:13fa80c527ef770e021563e121d5545b58c8ba02d9c19032ad0933242c473555","observation_id":"6dc57cd3-540b-4928-bbd9-11eb3dacbbec","resolution":{"observed_at":"2026-08-16T05:53:46.253206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.137223Z","title":"A comparison of four algo- rithms for change detection in an urban environment.Remote sensing of environment, 63(2):95–100, 1998","venue":null,"work_id":"087ef4f8-7e0c-418f-9dbe-8e3b9ce4ac3d","year":1998},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.482683Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:e233561048a8f5208000ae5cf4470406fd4eda4e4e66735a1127fa2c155861e2","observation_id":"9ae5f87c-c54c-4f5f-b993-f632fadf911c","resolution":{"observed_at":"2026-08-16T05:53:46.142293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.121294Z","title":"Multi-temporal scene classification and scene change detection with correlation based fusion","venue":null,"work_id":"56fc455d-3831-4f40-89b7-93550cd13322","year":2020},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.515516Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:aa9ab0e8a279feeac961f695557ed11cfd63993855780083053c2bc474581b0f","observation_id":"d5d100e8-067d-4182-a2a6-2de43da9400f","resolution":{"observed_at":"2026-08-16T05:53:46.126533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.104894Z","title":"Mobilenetv2: Inverted residuals and linear bottlenecks, 2019","venue":null,"work_id":"bd94b765-78c8-414f-8495-0eb9e32cdc1b","year":2019},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.552545Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:63e568301fa861238ec23a3dc9561edcf54b6b748c5e782c723317c5276de315","observation_id":"77049e9e-019a-4bec-9b0f-0cab40e8ea15","resolution":{"observed_at":"2026-08-16T05:53:46.109440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.088773Z","title":"Sunet: Change detection for heterogeneous remote sensing images 9 from satellite and uav using a dual-channel fully convolution network","venue":null,"work_id":"b4f8d8b5-151c-4417-8f99-0211a48d2562","year":2021},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.621701Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:a13e99481307587f0848040991e81599feb1540968874bd8ac28120eb06cdf3e","observation_id":"23a80446-f147-490e-adca-df65b935ba4c","resolution":{"observed_at":"2026-08-16T05:53:46.094002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.073319Z","title":"A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection","venue":null,"work_id":"18248c4d-7eb7-4dd9-9640-3472f09d8216","year":2021},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.651402Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:52a35698ccceb8199a94ae1a7b0cda5c32617228a2a989e1fe0cd49005ef57ea","observation_id":"102f3cc6-8f01-478f-89e9-7d7b9d34b38e","resolution":{"observed_at":"2026-08-16T05:53:46.078818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.057901Z","title":"Change detection based on artificial intel- ligence: State-of-the-art and challenges","venue":null,"work_id":"6c04eaf5-d2d9-4019-9a7d-25d0046ebcd0","year":2020},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.690263Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:a8c798a0a04896b475e01ce2308cef5f27574f1aab51a40d3731be4c5d523e45","observation_id":"e7e03869-2b6f-4119-a05c-300602c0c934","resolution":{"observed_at":"2026-08-16T05:53:46.062998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:46.042314Z","title":"Review article digital change detection techniques using remotely-sensed data","venue":null,"work_id":"abfd467e-6df8-414b-a211-bc64365778b2","year":1989},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.725807Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:4c7b8714cc126141bb82c8d9c96212beb32b432d09c1d1abbf726883041d539d","observation_id":"75aa105c-2904-41a1-8691-8cf782e23e36","resolution":{"observed_at":"2026-08-16T05:53:46.047502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.730286Z","title":"Deep high-resolution representation learning for human pose es- timation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.730286Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:f2147929e904956348abdc93418bd40ae7355e93bc5e6cf4d5b0d2fbebdfc426","observation_id":"0b208ceb-7006-4d80-ae95-3c9acae74e22","resolution":{"observed_at":"2026-08-16T05:53:45.730286Z","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":"2026-08-16T05:53:45.734738Z","title":"Gomez, Lukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.734738Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:cb522e4d8f90519411dd13f1f8c81b27ddaf5073f5f993dd2ec13904c7d52453","observation_id":"be0caa82-edb3-4fba-a6d5-868ff433933a","resolution":{"observed_at":"2026-08-16T05:53:45.734738Z","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":"2026-08-16T05:53:45.738957Z","title":"Cbam: Convolutional block attention module","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.738957Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:ee7c3b23d23bc52b5fa5d7ae0fa8672cfbd3f4c68ddb9fc450e301e04c5e4c1b","observation_id":"54aa8968-be6a-4802-af57-2883c184bb3f","resolution":{"observed_at":"2026-08-16T05:53:45.738957Z","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":"2026-08-16T05:53:45.998754Z","title":"Change detection based on deep siamese convolutional network for optical aerial images","venue":null,"work_id":"a8e7b6b3-2187-44f2-a226-0af9d5a4fdc1","year":2017},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.742859Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:28004b34da2e8228975daa800ab4d2d81c248790994f2da155992a56a78bd61b","observation_id":"fa100a80-2354-4e95-a738-fcbc9a371889","resolution":{"observed_at":"2026-08-16T05:53:46.003137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.931201Z","title":"Swinsunet: Pure transformer network for remote sensing im- age change detection","venue":null,"work_id":"0d7ca162-1d43-44f4-832b-0545ec74c7d5","year":2022},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.746788Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:6e9a61c990064d6107e248764e39ac595a2026bbbda204d755b74998a167e9e1","observation_id":"929b3673-1518-422c-9616-5d76058df72b","resolution":{"observed_at":"2026-08-16T05:53:45.969484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.898115Z","title":"Escnet: An end-to-end superpixel-enhanced change detection network for very-high-resolution remote sensing images","venue":null,"work_id":"95fef60e-4b6a-4862-8836-bc8422f282f6","year":2021},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.750998Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:73ccfd431c08d28b442aa01b02724281f926c16366a40c6cdf405d97638d505b","observation_id":"acea9505-1078-4a5a-b7e5-de7f6d7deea5","resolution":{"observed_at":"2026-08-16T05:53:45.902963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.882256Z","title":"Relation changes matter: Cross- temporal difference transformer for change detection in re- mote sensing images","venue":null,"work_id":"6a1f4658-e9fb-45c9-ba30-09fc2ea18892","year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.754950Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:f09a56c91fde2a89f17887ebf9432fc7a8a523666ba07d815d21916964a329b5","observation_id":"4755537b-f8fd-48a0-a32c-71d731c74106","resolution":{"observed_at":"2026-08-16T05:53:45.886977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.867549Z","title":"Triplet-based semantic relation learning for aerial remote sensing image change detection.IEEE Geo- science and Remote Sensing Letters, 16(2):266–270, 2018","venue":null,"work_id":"82c5015d-45ca-499b-bd90-4b1fadaed590","year":2018},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.759431Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:d53f112eaa7be675c410b901c4442f5e9f465693b1d95273c5399dfd6fc1dbdd","observation_id":"3aa87f71-ba68-4909-a9e1-668aa72be484","resolution":{"observed_at":"2026-08-16T05:53:45.871807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.853351Z","title":"Change is everywhere: Single-temporal supervised object change detection in remote sensing imagery","venue":null,"work_id":"1aa5b46d-f951-4959-a48f-ed5856111457","year":2021},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.763330Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:7bfa08eeed00c5eb219cf57c92961e8530effc1f8b886608cbc07052ec2d3a92","observation_id":"208c7b3e-65c4-4360-9c07-39024f0e94e2","resolution":{"observed_at":"2026-08-16T05:53:45.858140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.837729Z","title":"A multiple conditional random fields ensemble model for urban area detection in remote sensing optical images","venue":null,"work_id":"0972c40b-aa8e-4e77-90ba-5002b91b0a9e","year":2007},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.767962Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:68fde9953b5f3d99f60c2ee5d45da8864a87a34fa123423a2edb4df681bc25b2","observation_id":"e0272709-8a40-4cdf-a225-2820eafb58da","resolution":{"observed_at":"2026-08-16T05:53:45.842897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-16T05:53:45.821360Z","title":"A unified deep learning network for remote sensing image reg- istration and change detection","venue":null,"work_id":"b9e4f50a-9ad9-434f-86e0-ffedf3072f71","year":2023},"citing_paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-16T05:53:45.772547Z"},"links":{"citing_paper":"/paper/2504.19598"},"observation_digest":"sha256:62e24287940fb9d1da9cca9e5a3a36e901ec497476b2b97f4db7ae5c2f72efbe","observation_id":"7799308c-1b8f-4ff9-a6fd-c5c5ffd0126b","resolution":{"observed_at":"2026-08-16T05:53:45.827611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.19598","last_updated":"2025-04-28T09:01:56Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T05:46:12.690223Z","submitted_at":"2025-04-28T09:01:56Z","title":"Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":0,"verified_fuzzy":41},"total_outbound_references":49},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2504.19598."}