{"as_of":"2026-08-22T03:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8533027d345655fd1a0357a380fe35cba6859a08160c17a4dfa9df3f9f9f34d9","coverage":[{"denominator":80,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":80,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-14T21:05:19.119233Z","state":"measured"},{"denominator":81,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":81,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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":"2026-08-01T09:29:08.519197Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"cited_work":{"arxiv_id":"2605.12678","doi":"10.48550/arxiv.2605.12678","metadata_source":"pith","pith_arxiv_id":"2605.12678","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","venue":"cs.CV","work_id":"8d52f679-6294-44c8-8d95-44764e5f7537","year":2026},"citing_paper":{"arxiv_id":"2607.20778","last_updated":"2026-07-22T23:00:02Z","snapshot_observed_at":"2026-08-19T19:37:55.248317Z","submitted_at":"2026-07-22T23:00:02Z","title":"Toward Mechanistic Interpretability of an AI Foundation Model Fine-Tuned for Atmospheric Chemistry","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-01T09:29:08.519197Z"},"links":{"cited_paper":"/paper/2605.12678","citing_paper":"/paper/2607.20778"},"observation_digest":"sha256:a22a02a1bacac1bf177789779c4f49b7789498f3c4c32f52775f9aa83dfdd3d9","observation_id":"cff72548-152d-47e3-b811-02dea5416d50","resolution":{"observed_at":"2026-08-01T09:33:38.989768Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2605.12678/citation-record","integrity":"/paper/2605.12678/integrity","json":"/paper/2605.12678/citation-record.json","paper":"/paper/2605.12678"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Omnisat: Self- supervised modality fusion for earth observation","venue":null,"work_id":"3598560f-1212-4c51-b9f1-01949dad899a","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:73413efbf506d949a3919b725d21507a844e342bd5c3b81502a9a5c9d44eb89e","observation_id":"a0edf6d3-3b7a-4580-a061-c1f286e6db7f","resolution":{"observed_at":"2026-05-15T12:40:36.878085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Anysat: One earth observation model for many resolutions, scales, and modalities","venue":null,"work_id":"119f2590-facb-4403-b817-c656fe179c23","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:712c578e95083204115ae5b40b16f2f0117a0f5851dc2fe43e9aeb189045057b","observation_id":"d060de42-69e7-4aa5-9ce9-2af41d405a7b","resolution":{"observed_at":"2026-05-15T12:40:36.870223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Satlaspretrain: A large-scale dataset for remote sensing image understanding","venue":null,"work_id":"f5130711-cf5d-401f-8fb8-7ef5d63c5a63","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:6ed23191a4ac4cd992994495fb0e0137bd0f8a59a1905e338569489383c36843","observation_id":"cb40aa3d-6afe-42f3-b166-7ae89f808182","resolution":{"observed_at":"2026-05-15T12:40:36.862522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Olmoearth: Stable latent image modeling for multimodal earth observation","venue":null,"work_id":"39985f20-f64a-4024-b898-83be61ca9c84","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:2e2fc3aeb619a7af5e85426616ac0a30448760ed880578fd72e2b941be9db970","observation_id":"9b4c4b56-fb2c-4135-96bc-ca91e226e20b","resolution":{"observed_at":"2026-05-15T12:40:36.867103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07258","last_updated":"2022-07-12T23:45:14Z","snapshot_observed_at":"2026-08-02T09:20:40.804790Z","submitted_at":"2021-08-16T17:50:08Z","title":"On the Opportunities and Risks of Foundation Models","version":3},"cited_work":{"arxiv_id":"2108.07258","doi":"10.1016/j.specom.2008.12.003","metadata_source":"pith","pith_arxiv_id":"2108.07258","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"On the Opportunities and Risks of Foundation Models","venue":"cs.LG","work_id":"a18039e9-928d-47c9-a836-32656a71bf71","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2108.07258","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:3739626c7080ce505da4ddd07aa6f33dafcffb1217e7c2d807bb4f336e330280","observation_id":"44247a12-586a-4020-9694-770273705155","resolution":{"observed_at":"2026-05-14T21:19:28.509360Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-05-24T09:22:59.787075+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T09:22:59.787075+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/aaai","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T02:04:26.079898Z","title":"Louis, G","venue":null,"work_id":"9f349f1f-0e39-446f-8ac6-694a06c25de5","year":2026},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:32b4cf3f9358f13a93073314381298ddbeffcdb754a16bac8281850e1b5b9d99","observation_id":"f0c21e57-14df-439f-9abf-6d9a0d33049d","resolution":{"observed_at":"2026-05-14T21:07:58.939577Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Unreproducible research is reproducible","venue":null,"work_id":"833e1514-95f2-42b3-a8a5-5a2308ddaae9","year":2019},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:a8e823c87a5d655dc3134346e771b6407d72ac9e59a29aed10ab0c45d28a9941","observation_id":"60fd4dae-557f-4fcf-a017-87a0ba5bf241","resolution":{"observed_at":"2026-05-15T12:40:36.875390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Accounting for variance in machine learning benchmarks","venue":null,"work_id":"68bb6351-e0fe-4195-92ef-6fc4c37f92cb","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:348f018fa96ba6e9138d896898ae0dca5b25cd9379ecb57c4bc81f252ab5da2c","observation_id":"2bb40915-4d77-41f2-991b-8644d307602b","resolution":{"observed_at":"2026-05-15T12:40:36.872395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.22291","last_updated":"2025-09-08T19:42:30Z","snapshot_observed_at":"2026-08-14T08:27:53.538175Z","submitted_at":"2025-07-29T23:55:00Z","title":"AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data","version":2},"cited_work":{"arxiv_id":"2507.22291","doi":"10.3390/app15137056","metadata_source":"pith","pith_arxiv_id":"2507.22291","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data","venue":"cs.CV","work_id":"86dc003c-e312-4f37-9b21-36673f0ffca8","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2507.22291","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:cd81c6247a246e6794e2fc9532103d231a54d61fa791431953ff5f1a980a8663","observation_id":"0049b0d9-8eca-432e-ad9b-699b51a61db4","resolution":{"observed_at":"2026-05-17T21:13:43.902893Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-07-15T15:20:15.033294+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-15T15:20:15.033294+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-10T16:57:25.332055Z","title":"Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901","venue":null,"work_id":"bd7ec542-9242-446e-955e-bb75e729be5d","year":1901},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:171b1589b88f0dce90cee79dbf131c3be5c776bf900e196a22bc5390a7860a5e","observation_id":"4fc8c856-a8e3-4fc4-a3f6-e0950de06229","resolution":{"observed_at":"2026-05-15T12:40:36.760000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-11T02:27:52.995100Z","title":"Emerging properties in self-supervised vision transformers","venue":null,"work_id":"def40bfd-07b5-4f25-94fd-883b4ac6838d","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:4618741dba72d380a68f65510499237fddbb6e33d6352f68f06b68f03cff9928","observation_id":"40eea8b5-7d67-4923-9b6d-0fd8733a0f7a","resolution":{"observed_at":"2026-05-15T12:40:36.730868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts","venue":null,"work_id":"ea843fdc-96b0-475f-b566-1561d497bbfb","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:d9b9c6c6ba497e47158997fc349d613cb5424b0e49ce7f40ad3f418a8712e0bb","observation_id":"e626e6f8-f93c-4e68-bf10-16efa38ff995","resolution":{"observed_at":"2026-05-15T12:40:36.847126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Remote sensing image scene classification: Benchmark and state of the art.Proceedings of the IEEE, 105(10):1865–1883","venue":null,"work_id":"b5a89d2a-b5de-426b-b602-f947033259a5","year":2017},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:58790ea771698ca6bc513683809f26114d7be7bc22a29de9248a1be52b322123","observation_id":"eaad0c00-fed7-4b44-b4fd-9989dfb3048e","resolution":{"observed_at":"2026-05-15T12:40:36.857535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Functional map of the world","venue":null,"work_id":"b760f89e-b194-46d1-afe9-9ad98241c6f8","year":2018},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:4affdcc2c29f2eadea186351e56229c21dec3678ee93624e47862a882c28fc94","observation_id":"5a6b48c4-6650-4e27-849e-afff6bac38e0","resolution":{"observed_at":"2026-05-15T12:40:36.833004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"3382.2024","doi":"10.1109/cvprw63382.2024","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Work- shops (CVPR W), pp","venue":null,"work_id":"aced34f9-871a-4ea9-8cac-1b541bdb3edd","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:7db758ee4b80990b7bfa2255d6e56056f2aba75454119d532a79d8a4ac827ebe","observation_id":"71337712-7af4-4a90-90fa-629681ce2912","resolution":{"observed_at":"2026-05-14T21:19:28.518439Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.06281","last_updated":"2025-06-06T17:59:50Z","snapshot_observed_at":"2026-08-19T23:06:17.502694Z","submitted_at":"2025-06-06T17:59:50Z","title":"TerraFM: A Scalable Foundation Model for Unified Multisensor Earth Observation","version":1},"cited_work":{"arxiv_id":"2506.06281","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.06281","snapshot_observed_at":"2026-07-04T10:29:44.855067Z","title":"arXiv preprint arXiv :2506.06281 (2025)","venue":null,"work_id":"ddb00ec1-f608-4b64-9eb4-5fb33db03cbf","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2506.06281","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:4214c1555e10096e805dcc1fc93e83173457c7364b3c171883bd309ed7b46155","observation_id":"0f7f6242-c470-46f8-86e1-1617face2287","resolution":{"observed_at":"2026-05-14T21:19:28.505309Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.07002","last_updated":"2021-07-14T21:08:30Z","snapshot_observed_at":"2026-08-19T06:03:25.160551Z","submitted_at":"2021-07-14T21:08:30Z","title":"The Benchmark Lottery","version":1},"cited_work":{"arxiv_id":"2107.07002","doi":"10.48550/arxiv.2107.07002","metadata_source":"arxiv_reference","pith_arxiv_id":"2107.07002","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chunyuan Deng, Yilun Zhao, Xiangru Tang, Mark Gerstein, and Arman Cohan","venue":"arXiv (Cornell University)","work_id":"2662531a-bd8c-4a98-9104-354aba180472","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2107.07002","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:9169dd41ff8590116a448cb642ac69b0b8a376a544bef5cb7fc0c538f6dea439","observation_id":"af9c5416-b4e6-4061-ba84-e120816aca31","resolution":{"observed_at":"2026-05-14T21:19:28.538296Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-09T06:36:03.268346Z","title":"Imagenet: A large- scale hierarchical image database","venue":null,"work_id":"6ee29c54-0013-4f3e-8bcb-5c870412e0cb","year":2009},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:6576f17862dbbd4b03078b3af600dc245e682e1ed939559a6a13c5dad317d05b","observation_id":"382ff242-2b64-4847-a01e-54ed1736193f","resolution":{"observed_at":"2026-05-15T12:40:36.765017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-09T10:36:10.633869Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding","venue":null,"work_id":"1bdc18bb-17d9-44c5-8f2b-ca096572a66b","year":2019},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:976b64e90c8840f8f34a3913884db4353ba91839a7289217f7bf64a19b1bd42c","observation_id":"76e831cc-8441-454a-8d28-5daedf40d00d","resolution":{"observed_at":"2026-05-15T12:40:36.767618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Data science at the singularity.Harvard Data Science Review, 6(1)","venue":null,"work_id":"8f7362ad-8b64-44b8-b4a6-36ed723bdf5c","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:d566473e045764f6d6cc730f9a0682a73b8c6ef20f482076f4b3807b2a323058","observation_id":"2a30831f-11bd-4a99-8857-5626637b5e54","resolution":{"observed_at":"2026-05-15T12:40:36.829996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2010.11929","doi":"10.1175/jcli-d-22-0357.1","metadata_source":"pith","pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","venue":"cs.CV","work_id":"e96730e3-129b-4db6-b981-15ab7932e297","year":2020},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:a19d87db554c455779122adcf469108b9d95545d09ffd8fd4ee23212933fb373","observation_id":"57a56fdd-0239-4c91-94e8-54bbfae81e84","resolution":{"observed_at":"2026-05-14T21:19:28.513379Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Phileo bench: Evaluating geo-spatial foundation models","venue":null,"work_id":"84637f77-efe5-466a-8817-72325c7ce1ed","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:02bbbdf94b2855a2efbb7d9eef982733a63ecbeac013862495a80fa8bb45b6a7","observation_id":"0898ed4d-7164-47f2-bee5-98d31e4c9373","resolution":{"observed_at":"2026-05-15T12:40:36.757280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Open LLM leaderboard v2","venue":null,"work_id":"e91cd273-323a-4f78-aef1-7d9cab9192f0","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:9d48c26b9dc135176afc23e5878cb1f05174642f2386a11af923b33057717c3e","observation_id":"40517f73-0a5d-40e6-85a4-ef17a3bdb6c3","resolution":{"observed_at":"2026-05-15T12:40:36.810419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Major tom: Expandable datasets for earth observation","venue":null,"work_id":"eb9e8892-b5e9-47ba-b8ce-f5a0b2c5f809","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:b5174de42b620cb6aa5c331f7a207c9db480906882b0ed44c54a227f7202a5aa","observation_id":"a58486f5-0eef-4a0a-a447-e722d54025b9","resolution":{"observed_at":"2026-05-15T12:40:36.813067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Bad tables: Why you shouldn’t trust results tables in remote-sensing founda- tion model papers","venue":null,"work_id":"43df4443-aa6b-46f3-a4dc-b656ddc8941c","year":2026},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:e783dd9b1310c0a1ddbe7dbe056e3cfe46b60c4985c65db7c3fbce6c6eefa4cc","observation_id":"d67023b5-20fc-4c12-a874-b1182cebf471","resolution":{"observed_at":"2026-05-15T12:40:36.864905Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Croma: Remote sensing representations with contrastive radar-optical masked autoencoders.Advances in Neural Information Processing Systems, 36:5506–5538","venue":null,"work_id":"184173ae-64ee-4116-8f46-d25618520310","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:32fef97d5288170a5a5be2d8fbec3f06f89a242b36077a58850b45493e4de63b","observation_id":"0dadcf74-fd4f-4dbf-ab7b-ff93896d355a","resolution":{"observed_at":"2026-05-15T12:40:36.807846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"A framework for few-shot language model evaluation.Zenodo, 2024.lm-evaluation-harness","venue":null,"work_id":"022cfd02-9d9a-46ea-a739-0af689aa9eed","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:d3388a4860994f8efb0628e2c2a54c1e49df6336381fbe324b83dfe957ebca34","observation_id":"9851bbc2-8023-43ea-838f-0f25d9e0d354","resolution":{"observed_at":"2026-05-15T12:40:36.775284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Flair: a country-scale land cover semantic segmentation dataset from multi-source optical imagery.Advances in Neural Information Processing Systems, 36:16456–16482","venue":null,"work_id":"84a4cc7c-2aa0-4e22-a9be-0f106f48a05a","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:315910e0e0fb5abd453d6268dbeaf67505836a292aae100353b8cc629e3a80cd","observation_id":"0863d5ed-774e-4fb0-b584-9e1b0c4bf103","resolution":{"observed_at":"2026-05-15T12:40:36.777960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Terratorch: The geospatial foundation models toolkit","venue":null,"work_id":"775ecde5-9c11-426c-9d37-96fa5dbb9575","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:7ef1df18224c7548de39890e13ef969ce55d8c9bbb7b7e3bc3e72ff2494a2519","observation_id":"7faec46e-51f2-4fb7-bcf7-3a4bff8cf022","resolution":{"observed_at":"2026-05-15T12:40:36.801679Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Deep residual learning for image recognition","venue":null,"work_id":"75056d48-17da-4303-b23f-0ff702ed5213","year":2016},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:0c7d503f836ffd8e770abc8bf237fb46322dd0cae7a476394ab45c1ec0425298","observation_id":"555829fd-8698-4471-9ce2-44029ffcdd74","resolution":{"observed_at":"2026-05-15T12:40:36.804701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"e7fef07c-2639-4dd3-b58f-49006238b181","year":2019},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:8540be8c9ff8561a67f394a23ed315562b765356268b537eb6bbd8dc8bf47ba3","observation_id":"94cd179c-76d4-4917-99a1-9a75a70049cd","resolution":{"observed_at":"2026-05-15T12:40:36.839574Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.20776","last_updated":"2026-08-17T11:38:31Z","snapshot_observed_at":"2026-08-20T23:15:29.447788Z","submitted_at":"2025-07-28T12:39:33Z","title":"RingMo-Agent: A Unified Remote Sensing Foundation Model for Multi-Platform and Multi-Modal Reasoning","version":3},"cited_work":{"arxiv_id":"2507.20776","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.20776","snapshot_observed_at":"2026-08-18T03:17:13.055583Z","title":"RINGMO-Agent: A unified remote sensing foundation model for multi-platform and multi-modal reasoning.arXiv preprint arXiv:2507.20776","venue":null,"work_id":"b1aadc19-4429-49ba-941b-9634601248e6","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2507.20776","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:b8c2359a6842b4133e09c04a681943783aecfa4fdc46a352fe903c06d337e099","observation_id":"ce5f74fb-caef-4306-9f86-bc178592cf6c","resolution":{"observed_at":"2026-08-18T03:17:13.055583Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Mdas: A new multimodal benchmark dataset for remote sensing.Earth System Science Data, 15(1):113–131","venue":null,"work_id":"5237d310-fd46-45eb-8709-e52ea2b5a294","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:1d78452fda9c3e8fe4b78ac45fae40dbbe321d1f410d5137b637aa3f3462b513","observation_id":"1efcd4bc-ffe3-4099-ab56-21d4e8076a19","resolution":{"observed_at":"2026-05-15T12:40:36.716337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Generic knowledge boosted pretraining for remote sensing images.IEEE Transactions on Geoscience and Remote Sensing, 62:1–13","venue":null,"work_id":"9dd34a2b-2a8b-404d-82ac-e7493e0f6055","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:8d90f8a63d49d25f9213918f7c95f1c0c02dc4e1daa8606e299300601a5c9b63","observation_id":"97dee1d0-5015-436a-9d54-bbcb380403d7","resolution":{"observed_at":"2026-05-15T12:40:36.718707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"288ddb76-c261-4cee-9c67-459de7728e5f","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:653dc96a2662983e1cb8dd184021395512bbfa0df1af303bec356c24b67dc513","observation_id":"2d1f5a7a-b0dc-4340-8d86-f13dcda92ea0","resolution":{"observed_at":"2026-05-15T12:40:36.797821Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10994-021-05972-1","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spatial depen- dence between training and test sets: another pitfall of classification accuracy assessment in remote sensing.Machine Learning, 111:2715–2740","venue":"Machine Learning","work_id":"97198b94-8ad1-4795-bb34-d9144a6e77ef","year":2022},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:dcc85d533ae05ffc2b7fd7e0d12ed992cbee2dbad95c070e2cf9f498ca933321","observation_id":"5ec92147-ad9d-4d78-8e67-4373839b2333","resolution":{"observed_at":"2026-05-14T21:07:58.935773Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2022.100018","doi":"10.1016/j.ophoto.2022.100018","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mahecha, and Carsten F","venue":"ISPRS Open Journal of Photogrammetry and Remote Sensing","work_id":"545f70e7-ac7c-40b0-bdc3-e1fa23fdb089","year":2022},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:b24a7b1b6a0c7401aa058829b81001acc770fc76f30c434e27b57acc65f93d8b","observation_id":"d481643a-361a-42b8-aabc-4378c5e50081","resolution":{"observed_at":"2026-05-14T21:07:58.932512Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.21104","last_updated":"2026-04-22T21:43:03Z","snapshot_observed_at":"2026-07-06T23:07:47.244208Z","submitted_at":"2026-04-22T21:43:03Z","title":"Pretrain Where? Investigating How Pretraining Data Diversity Impacts Geospatial Foundation Model Performance","version":1},"cited_work":{"arxiv_id":"2604.21104","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.21104","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pretrain Where? Investigating How Pretraining Data Diversity Impacts Geospatial Foundation Model Performance","venue":"cs.CV","work_id":"907548da-1e6e-4d79-9315-3462b11fad46","year":2026},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2604.21104","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:df9395de15c85476878587ec9e5d75b06e8c405d86a847c2f95a67849c35e7a8","observation_id":"c1983ebc-f87e-407c-aefb-36fefc7a5881","resolution":{"observed_at":"2026-05-14T21:19:28.544554Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-11T02:27:53.204657Z","title":"Segment anything","venue":null,"work_id":"ccc0c322-2f90-4398-aaac-1d329cfcf543","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:bef93a1ba95f03aeb41ef463b8a8eb6b1eaa15dcc1f0ef981efd7e2ef2a2fe7c","observation_id":"a7093ad0-c256-43ba-8adf-078e14a31fb8","resolution":{"observed_at":"2026-05-15T12:40:36.816021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"2fe5c220-0b6b-49ac-bd13-3a96bb476560","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:4f567884d02ac7f73e0847da2e9a9ad2a0208d4228dd2f53620c585fc853f8d3","observation_id":"06e242ef-7355-4a78-8dd1-b5974c4eb272","resolution":{"observed_at":"2026-05-15T12:40:36.744280Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"GEO-Bench: Toward foundation models for earth monitoring","venue":null,"work_id":"2c5857a8-d116-4527-acc3-4f209c544f28","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:eda0ab62aa068b98e71b16827e417042fb64439133fbec650cfecd2ba4692c6c","observation_id":"96680da7-3927-4fb3-a606-06e840876870","resolution":{"observed_at":"2026-05-15T12:40:36.711082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Geo-bench: Toward foundation models for earth monitoring.Advances in Neural Information Processing Systems, 36:51080–51093","venue":null,"work_id":"0f3e661c-fa35-4d6d-abf9-a513b0a7e289","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:93b72cc575767e175d4804e808f75c74b7b8b33d06e604c25da13e0fff1da181","observation_id":"dfc040db-e8dc-400c-894e-0f5234573a3f","resolution":{"observed_at":"2026-05-15T12:40:36.769992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Object detection in optical remote sensing images: A survey and a new benchmark.ISPRS journal of photogrammetry and remote sensing, 159:296–307","venue":null,"work_id":"85c333c8-c17c-48f2-b17f-eb84541381da","year":2020},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:e26b34b64facfe985557698f60b8031d3160563953914ff9c83505e82480bde6","observation_id":"ed19b267-0f49-4b0a-b489-fad1744b453e","resolution":{"observed_at":"2026-05-15T12:40:36.849871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Masked angle-aware autoencoder for remote sensing images","venue":null,"work_id":"91c9ace3-ad80-4130-8199-8812a7e9f782","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:0f6d9b94cc33a01911bf5e7eef50e7ac813ce004c246628f17d08f5f06c5a95f","observation_id":"23d31581-85e4-4215-aef6-c57e569afd8f","resolution":{"observed_at":"2026-05-15T12:40:36.753054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Holistic evaluation of language models","venue":null,"work_id":"a0b91329-c39a-40f8-8b9f-7a5475ce8dbb","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:a22bd5db2357f2c8fd81bd25bdf7cd2fe3922a805672aaff6d8e9a6248e61520","observation_id":"b303df0c-a8c6-4705-846e-aebbb4936d03","resolution":{"observed_at":"2026-05-15T12:40:36.790256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Troubling trends in machine learning scholarship: Some ml papers suffer from flaws that could mislead the public and stymie future research","venue":null,"work_id":"8160340b-8391-4c7a-944d-51e38a8b1919","year":2019},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:a00b831b3b236d0548d8e02efaec47177fe75753d2b8d6e1b0d598815d723b5d","observation_id":"ae77a52c-9e60-431b-8432-a4a2cfa7a612","resolution":{"observed_at":"2026-05-15T12:40:36.762461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.17887","last_updated":"2025-01-27T19:40:00Z","snapshot_observed_at":"2026-08-15T15:32:18.722307Z","submitted_at":"2025-01-27T19:40:00Z","title":"Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion","version":1},"cited_work":{"arxiv_id":"2501.17887","doi":"10.48550/arxiv.2501.17887","metadata_source":"arxiv_reference","pith_arxiv_id":"2501.17887","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Docling: An efficient open- source toolkit for ai-driven document conversion","venue":"ArXiv.org","work_id":"d139a974-3108-4df8-89d1-c9c1e87ecfd4","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2501.17887","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:fbeea339f8b9428d453872b7c7903b49d57dfce92ec9c6c50dc1a46d87509fa0","observation_id":"2a7b40cf-15a7-4737-a2d3-674798c35f95","resolution":{"observed_at":"2026-05-14T21:19:28.523157Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"de274260-00f2-49ba-b1ef-12566541bd6d","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:ecb5195a2ce8f7058e4bdc413daf4f1eb51fa2401f04b9b9d5c8a881f3fdcc4a","observation_id":"b8fad2e1-b6c5-47d3-9871-bf4fc31a0dcc","resolution":{"observed_at":"2026-05-15T12:40:36.780097Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Zimmer-Dauphinee, et al","venue":null,"work_id":"436addad-d7b7-4a48-acd2-f450f2c5fa7a","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:3d481dd57136aa88776f22ff79297e9fb03a84e703e0585e77e4f85140fa7a5d","observation_id":"66b4b306-2ede-44ef-9bfe-8c69df12878a","resolution":{"observed_at":"2026-05-15T12:40:36.737546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Sea- sonal contrast: Unsupervised pre-training from uncurated remote sensing data","venue":null,"work_id":"bb747b59-6889-4708-baa5-85e5dadaa845","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:d6d6f5b4617f3005ef24ae698090808000cef42128ea64db1a23bc07381652e5","observation_id":"4a8996d7-a21f-4c7f-bff6-e4d3c96d65cf","resolution":{"observed_at":"2026-05-15T12:40:36.728449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04204","last_updated":"2025-04-30T08:17:21Z","snapshot_observed_at":"2026-08-17T18:45:46.162385Z","submitted_at":"2024-12-05T14:40:41Z","title":"PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models","version":2},"cited_work":{"arxiv_id":"2412.04204","doi":"10.48550/arxiv.2412.04204","metadata_source":"pith","pith_arxiv_id":"2412.04204","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Pangaea: A global and inclusive benchmark for geospatial foundation models","venue":"cs.CV","work_id":"b4e3e568-3779-45f9-a778-9709ef392ffc","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/2412.04204","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:e0cb9bb7cd36508c71574fe6d376a265ac1450b0c6cf15ee21ea585a2a7b0c19","observation_id":"99530bea-e428-4990-94fe-2b0281aea3b0","resolution":{"observed_at":"2026-05-14T21:19:28.534901Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Towards geospatial foundation models via continual pretraining","venue":null,"work_id":"59098358-3171-4832-970b-f0615ad0c236","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:4f49bbcf226884c2d3d56b72338c4fa8e97a94d10b894243bb948224528f53e5","observation_id":"1607ebf2-dbee-4e1f-9cc5-574b9ba635e9","resolution":{"observed_at":"2026-05-15T12:40:36.746730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Mmearth: Exploring multi-modal pretext tasks for geospatial representation learning","venue":null,"work_id":"5c078131-c4c9-4579-ad4c-681a40be525f","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:016f8759de76ddbc04865b089259c8e0dcd693ed4546dfe76ae8b5a5145905db","observation_id":"32b50ae9-29f7-4383-bb11-25708e28dd49","resolution":{"observed_at":"2026-05-15T12:40:36.784678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Mapping global dynamics of benchmark creation and saturation in artificial intelligence.Nature Communications","venue":null,"work_id":"f9b53782-cac8-4b18-ac5b-cb8a80db01c7","year":2022},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:6a6d1dbee1d0e963f36c3247b163370f4f12fb12242ce4b689d95de2a12fc3d5","observation_id":"e542af89-c7ba-4ee8-885f-65c451e1ab80","resolution":{"observed_at":"2026-05-15T12:40:36.852287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Planted: a dataset for planted forest identification from multi- satellite time series","venue":null,"work_id":"e0265959-5136-496b-8f1c-80c3c5b3b14d","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:5d4e0f26f49cd1108a406c4e6a1617773047bbda124eb07fb8d725cf9df12970","observation_id":"e96143e1-6777-487b-93a4-b5c8e7eecd78","resolution":{"observed_at":"2026-05-15T12:40:36.787099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-09T07:16:04.687562Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"ad3e05b3-af3a-4fa2-ab30-c45f9f403277","year":2021},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:9d07df1c72ba14b417ee029097b4ccbd80b2df6230f8c5aeea3415473fb7cf3b","observation_id":"42d204cb-0082-4151-8ccc-212308eef071","resolution":{"observed_at":"2026-05-15T12:40:36.823016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Scale-mae: A scale- aware masked autoencoder for multiscale geospatial representation learning","venue":null,"work_id":"00df27d1-c271-44b1-9868-6c31586cf852","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:a56f41ec276bbf1968b3965ad9e0e5f908560471288736407073e8aac8f4960a","observation_id":"83f049e5-dd9d-44a0-bf2b-003805646ced","resolution":{"observed_at":"2026-05-15T12:40:36.819057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Position: Mission critical – satellite data is a distinct modality in machine learning.ICML","venue":null,"work_id":"b8dd3812-82fe-4409-9b4f-e630eed82dad","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:00e6022bcee3728570b0d83acedcbd9772c5c6fde404db2a8c4d5be52f2c7cc7","observation_id":"98a63e45-7ff2-4e2b-87ff-776b12403c1b","resolution":{"observed_at":"2026-05-15T12:40:36.782518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.07789","last_updated":"2019-06-18T20:21:41Z","snapshot_observed_at":"2026-08-17T22:00:05.926234Z","submitted_at":"2019-06-18T20:21:41Z","title":"SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion","version":1},"cited_work":{"arxiv_id":"1906.07789","doi":null,"metadata_source":"pith","pith_arxiv_id":"1906.07789","snapshot_observed_at":"2026-07-03T20:18:56.395474Z","title":"SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion","venue":"cs.CV","work_id":"6e9de9c0-8f4e-4380-8ffb-b7aa0544f8e3","year":2019},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/1906.07789","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:3ac99e81cc83cce69df55faba3008a8e15ab1c72a2bf58385e595ec7e297175f","observation_id":"e38e218a-b1c4-41e7-a3c7-5427a675799a","resolution":{"observed_at":"2026-05-14T21:19:28.541589Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Laion- 5b: An open large-scale dataset for training next generation image-text models.Advances in neural information processing systems, 35:25278–25294","venue":null,"work_id":"4d79c3b1-4122-4788-93f1-5590f1b118db","year":2022},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:c715e998c56bfff971f863c0a51a94ab7dffe7e0c5b6b940aeae796cd972c9fe","observation_id":"8ab75596-f5cf-49d6-8584-8fa790e6af26","resolution":{"observed_at":"2026-05-15T12:40:36.750920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning","venue":null,"work_id":"63bbd0b4-3abf-4164-97f8-e7660d58d9f4","year":2018},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:231d58311d1c2127b952536077d1c13678980a9bdec0c577d7570ed2275a8d22","observation_id":"db6fe9a1-c8b2-402b-828d-736831fd1dd4","resolution":{"observed_at":"2026-05-15T12:40:36.755192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2511.15658","doi":"10.48550/arxiv.2511.15658","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Geo- bench-2: From performance to capability, rethinking evaluation in geospatial ai","venue":"Open MIND","work_id":"39135659-0d5c-4e59-9b05-dc1ee8d057bd","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:002fe9309024a9c9f6b560bc2b4d3143fa8ae086e7c2d5555e6b6556020930d1","observation_id":"d515f8dc-f6c6-4b87-87fc-fa472b735754","resolution":{"observed_at":"2026-05-14T21:19:28.555252Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Earthdial: Turning multi-sensory earth observations to interactive dialogues","venue":null,"work_id":"53fcd44c-d090-4c7b-836f-15e71bbdfe77","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:1aefa1e19c9420b58b0c63bd9fd1453db90b4a9bf8ad66e0cad67c9b3eef80dd","observation_id":"5ac2b690-ff59-45ee-a2fc-abc517faaabe","resolution":{"observed_at":"2026-05-15T12:40:36.843761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Beyond the imitation game: Quanti- fying and extrapolating the capabilities of language models.Transactions on Machine Learning Research","venue":null,"work_id":"d74dc06b-26c7-4794-9fe4-0de3a030cbb7","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:1985be0aa400db721533d0c0a0b9819cc3d0d6fcb404945e9cb3ba62fc1deac8","observation_id":"41de7d3f-7946-4eda-be8c-d0dd9fcd4366","resolution":{"observed_at":"2026-05-15T12:40:36.721210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Torchgeo: deep learning with geospatial data.ACM Transactions on Spatial Algorithms and Systems, 11(4):1–28","venue":null,"work_id":"cfbdf0b7-edff-4cd8-9fab-c21d9746268f","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:afdee22566dc7e3acb891a9d32e7f304b28c3e8d76a476dc59ecb09d34fb39ac","observation_id":"8cb6e911-df06-4b64-930d-23653afea6ae","resolution":{"observed_at":"2026-05-15T12:40:36.713917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Fair1m: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery.ISPRS Journal of Photogrammetry and Remote Sensing, 184:116–130","venue":null,"work_id":"1c044442-f493-4a76-a75e-e438ea4dda3f","year":2022},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:e7f59c8904da20936031f919f82e0b899ec183c41ca8fe3ffc145fee873fdb6e","observation_id":"a3a5d7a0-6cee-4e72-9f1c-eb029e6f4d2a","resolution":{"observed_at":"2026-05-15T12:40:36.794322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"49d86dc4-7bd5-4dfb-99bd-48b293be6961","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:289590ba884388b2c22293084e8e389f328099c3ca4e73d6478e21b91fc4d05b","observation_id":"140d2877-0aaa-47af-9a23-f80baab81554","resolution":{"observed_at":"2026-05-15T12:40:36.748718Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Galileo: Learning global & local features of many remote sensing modalities","venue":null,"work_id":"f9437164-7325-4672-b12e-f6b15edc2bad","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:b9d15045325dddfe382c267f951b85b941c36bdcac57dda356536674b003acb3","observation_id":"c8a992ce-b45a-40ff-87bd-224e32829c47","resolution":{"observed_at":"2026-05-15T12:40:36.726153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Panopticon: Advancing any-sensor foundation models for earth observation","venue":null,"work_id":"aac48f51-ffcb-452d-a9d1-aba613d8cb40","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:da64945b3f55bfd5df1a75284ca010b1b89581bd1ae45864fe53738c491c8f60","observation_id":"62cd4bec-f4eb-42e1-a93f-d3c879def313","resolution":{"observed_at":"2026-05-15T12:40:36.772545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Harnessing massive satellite imagery with efficient masked image modeling","venue":null,"work_id":"b760fd35-f9a9-4bfc-ad48-530fbc751d17","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:dee28e4d2d509efee1de8153439974bd936362328d0b16018b8a76d49248cea0","observation_id":"cdc897a6-1205-406f-9fc5-b4a4252ceca5","resolution":{"observed_at":"2026-05-15T12:40:36.735448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"73cf4b17-7318-49b9-9014-9d058379aa87","year":2023},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:495fa9c5afa6c5f3b9f2609022fe2b6865b6ba5a65ce7c7a807a9cca5a3babbc","observation_id":"6c420ada-3e09-46ac-8cb9-25e75233ca83","resolution":{"observed_at":"2026-05-15T12:40:36.733224Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Aid: A benchmark data set for performance evaluation of aerial scene classification.IEEE Transactions on Geoscience and Remote Sensing, 55(7):3965–3981","venue":null,"work_id":"6efcdf45-a2e2-4ae0-a1b5-442fe9da6325","year":2017},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:e53e66ec36cafcbcc1687486d4a8f7ab625a1a307d873a5ecae2d70605d982e7","observation_id":"f29a37d7-5351-4f3f-9e97-788ef4ee6482","resolution":{"observed_at":"2026-05-15T12:40:36.739759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Dota: A large-scale dataset for object detection in aerial images","venue":null,"work_id":"d795ccc3-f9cb-43b8-92be-0074821f87b4","year":2018},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:4ec3815a6774343b0ea8c6c07a95089c18e81557dc7a97878efcede1583a086d","observation_id":"9fbfabfe-3fd3-4d4a-bc16-099b5792a92c","resolution":{"observed_at":"2026-05-15T12:40:36.742008Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Foundation models for remote sensing and earth observation: A survey.IEEE Geoscience and Remote Sensing Magazine","venue":null,"work_id":"2dab7bed-9663-43b4-874f-928db1b809c3","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:17b1620d5ce8f5471c09b001f159549b32599cc7fb68c9bba7d9ce1ad3fe8546","observation_id":"a15d6485-3688-4403-8600-da91ed7d9d33","resolution":{"observed_at":"2026-05-15T12:40:36.723609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2403.15356","doi":"10.48550/arxiv.2403.15356","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Xiong, Y","venue":"arXiv (Cornell University)","work_id":"3fe68a11-7152-4361-91fb-c3443e69b84d","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:9f7fa5ac2da6ef272b6ed9ee5275be99b15ad4bf832bf275dedf9601762c1ac8","observation_id":"6ff56765-c5a7-43c3-84b7-f0b018b91a42","resolution":{"observed_at":"2026-05-14T21:19:28.527792Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Bag-of-visual-words and spatial extensions for land-use classifi- cation","venue":null,"work_id":"8761cfc5-5cc1-44e9-904c-73e1969e2d35","year":2010},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:d2c53cb9f46881d0dd842e41190030845d32f46332599a4c3dcadaa94e747706","observation_id":"1510cdeb-fe04-4e83-aa06-a1c43645bf32","resolution":{"observed_at":"2026-05-15T12:40:36.826560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.04867","last_updated":"2020-02-21T13:36:15Z","snapshot_observed_at":"2026-08-09T06:48:42.729935Z","submitted_at":"2019-10-01T17:06:29Z","title":"A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark","version":2},"cited_work":{"arxiv_id":"1910.04867","doi":"10.48550/arxiv.1910.04867","metadata_source":"pith","pith_arxiv_id":"1910.04867","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark","venue":"cs.CV","work_id":"eb743d69-6704-47c1-bb0f-76520dd00c3d","year":2019},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"cited_paper":"/paper/1910.04867","citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:ad2c228e80330cfd5c5856ab82272990ade7bac03b2ed529ca4c02e638e4312d","observation_id":"ae39d87d-950e-411e-b00f-e4d58d9f1a54","resolution":{"observed_at":"2026-05-17T22:12:05.852900Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Ctxmim: Context-enhanced masked image modeling for remote sensing image understanding.ACM Transactions on Multimedia Computing, Communications and Applications, 21(12):1–22","venue":null,"work_id":"de2eb639-d844-4146-b621-2616f4680dd1","year":2025},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:ae7a53ae9fbb785d37b634a6cee3b9573183654c3824d3ed842b0682ce725d9c","observation_id":"204bfb40-b622-4ae8-8faa-29d00d2271cd","resolution":{"observed_at":"2026-05-15T12:40:36.836021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-09T15:06:18.884188Z","title":"Earthgpt: A universal multimodal large language model for multisensor image comprehension in remote sensing domain.IEEE Transactions on Geoscience and Remote Sensing, 62:1–20","venue":null,"work_id":"580e4482-e0c6-486e-9094-b16136a34a5c","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:7e530ae30c74263b6307d40d3ae09be2205761297810fcb3771f409443adfb10","observation_id":"88ba455b-d364-4db2-8b30-469cd9f33c30","resolution":{"observed_at":"2026-05-15T12:40:36.855103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-06-05T21:23:00.469572Z","title":"Rs5m and georsclip: A large- scale vision-language dataset and a large vision-language model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing, 62:1–23","venue":null,"work_id":"ed6ffb3d-8898-4541-b2ef-40e408e969bb","year":2024},"citing_paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-05-14T21:05:19.119233Z"},"links":{"citing_paper":"/paper/2605.12678"},"observation_digest":"sha256:f5c9e04b2b5056556c9f9b466bf498e901fd334ddfcdd1a0a9c4a30fa1ac5a3e","observation_id":"4073f9a6-a8b0-4718-9332-c55cf166f5b4","resolution":{"observed_at":"2026-05-15T12:40:36.860146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.12678","last_updated":"2026-05-12T19:29:51Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T14:39:16.211928Z","submitted_at":"2026-05-12T19:29:51Z","title":"No One Knows the State of the Art in Geospatial Foundation Models"},"reference_resolution":{"displayed":80,"state_counts":{"malformed_identifier":2,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":6,"verified_exact":13,"verified_fuzzy":57},"total_outbound_references":80},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 1 inbound Pith citation observation for arXiv:2605.12678."}