{"as_of":"2026-08-09T14:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0b55afab703e49b763a98670453144c8bfab4e1513664177b61e313b1e02ee36","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T10:14:30.161567Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T10:46:31.949402Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-08-08T10:14:30.161567Z","title":"arXiv preprint arXiv:2204.09868","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.08168","last_updated":"2025-03-04T01:07:55Z","snapshot_observed_at":"2026-08-08T10:09:38.252688Z","submitted_at":"2025-02-12T07:19:36Z","title":"SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR Image Interpretation","version":5},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-08T10:14:30.161567Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2502.08168"},"observation_digest":"sha256:ea680588d6a5f9c8309f7073c37b89b5032f1d883b3a2342a960ba35d06e9f2c","observation_id":"8827234e-7c7a-47e6-abe5-f09d1766d56f","resolution":{"observed_at":"2026-08-08T10:14:30.161567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-08-06T22:22:40.798399Z","title":"Exploring a fine-grained multiscale method for cross-modal remote sensing image retrieval,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21863","last_updated":"2025-06-27T02:31:37Z","snapshot_observed_at":"2026-08-07T01:10:13.747886Z","submitted_at":"2025-06-27T02:31:37Z","title":"Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modeling","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T22:22:40.798399Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2506.21863"},"observation_digest":"sha256:8a404b82f2e11680f183c8ffb0649b9d1402e55d6a4cc80bda02a260a316d71e","observation_id":"4911cca2-b81f-45e1-9d61-c6f362d666ac","resolution":{"observed_at":"2026-08-06T22:22:40.798399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-08-06T15:07:34.529414Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.16716","last_updated":"2025-07-22T15:54:53Z","snapshot_observed_at":"2026-08-08T05:30:53.359696Z","submitted_at":"2025-07-22T15:54:53Z","title":"Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:34.529414Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2507.16716"},"observation_digest":"sha256:e3411c798f968177bbca2fe59f7e3bc3c29d74ffc183fd61f1796525e1c94a88","observation_id":"b37f7e74-1af2-4020-9195-a83a2d0ae509","resolution":{"observed_at":"2026-08-06T15:07:34.529414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-08-05T10:27:19.319633Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05374","last_updated":"2025-09-04T11:39:22Z","snapshot_observed_at":"2026-08-05T10:27:19.036845Z","submitted_at":"2025-09-04T11:39:22Z","title":"A Synthetic-to-Real Dehazing Method based on Domain Unification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:19.319633Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2509.05374"},"observation_digest":"sha256:fadd03c40a610cde05cfc93626d73c5422afe108b2ff130287ab3943c17fdd5e","observation_id":"b46216a6-8104-4036-a563-6d422ed5dc3f","resolution":{"observed_at":"2026-08-05T10:27:19.319633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-08-04T10:22:46.080575Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.10180","last_updated":"2026-07-01T15:54:56Z","snapshot_observed_at":"2026-08-06T13:55:50.316117Z","submitted_at":"2025-10-11T11:38:01Z","title":"TCMA: Text-Conditioned Multi-granularity Alignment for Drone Cross-Modal Text-Video Retrieval","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T10:22:46.080575Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2510.10180"},"observation_digest":"sha256:f3d0a5c2270aa6e7d7e44ced3db8e89c1f1380b3d476ff20c92eb24c9a97634b","observation_id":"1f8653b5-b7cb-413b-8286-088ee138b522","resolution":{"observed_at":"2026-08-04T10:22:46.080575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":"2204.09868","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Exploring a fine-grained multiscale method for cross-modal remote sensing image retrieval","venue":null,"work_id":"add7a710-d978-4774-af52-802ee3012c08","year":2022},"citing_paper":{"arxiv_id":"2604.20429","last_updated":"2026-04-22T10:50:38Z","snapshot_observed_at":"2026-07-29T17:15:07.913186Z","submitted_at":"2026-04-22T10:50:38Z","title":"Fast-then-Fine: A Two-Stage Framework with Multi-Granular Representation for Cross-Modal Retrieval in Remote Sensing","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-10T00:02:12.727566Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2604.20429"},"observation_digest":"sha256:3fdab405e55795bd417dca74c161acc32e23a0c9ae75e0d8ce170bafb7dfa3c8","observation_id":"b65c5e9a-96bb-47af-a51f-579f08053517","resolution":{"observed_at":"2026-05-10T00:29:47.830027Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":"2204.09868","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Exploring a fine-grained multiscale method for cross-modal remote sensing image retrieval","venue":null,"work_id":"add7a710-d978-4774-af52-802ee3012c08","year":2022},"citing_paper":{"arxiv_id":"2604.22855","last_updated":"2026-04-22T12:28:04Z","snapshot_observed_at":"2026-07-06T23:09:10.050398Z","submitted_at":"2026-04-22T12:28:04Z","title":"Evaluating Remote Sensing Image Captions Beyond Metric Biases","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-10T01:06:35.604862Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2604.22855"},"observation_digest":"sha256:085cc2690f5932b0cafedd35cf2a9716dccb5ece12effd2a684f080e97f0f4c6","observation_id":"8d06f720-0d9b-474a-a6a2-bb44f910b2f7","resolution":{"observed_at":"2026-05-10T01:10:09.416375Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval","version":1},"cited_work":{"arxiv_id":"2204.09868","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2204.09868","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Exploring a fine-grained multiscale method for cross-modal remote sensing image retrieval","venue":null,"work_id":"add7a710-d978-4774-af52-802ee3012c08","year":2022},"citing_paper":{"arxiv_id":"2605.03189","last_updated":"2026-05-04T22:16:11Z","snapshot_observed_at":"2026-07-06T23:16:10.769968Z","submitted_at":"2026-05-04T22:16:11Z","title":"Sentinel2Cap: A Human-Annotated Benchmark Dataset for Multimodal Remote Sensing Image Captioning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T18:17:35.846352Z"},"links":{"cited_paper":"/paper/2204.09868","citing_paper":"/paper/2605.03189"},"observation_digest":"sha256:bcfa7a215a7e97b5b3d960a0202fbe6f26b82a01cbdaf9d19e5ea3aab69f9795","observation_id":"22af8262-01ea-4760-b32e-95edca020ccf","resolution":{"observed_at":"2026-05-12T10:46:31.952615Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2204.09868/citation-record","integrity":"/paper/2204.09868/integrity","json":"/paper/2204.09868/citation-record.json","paper":"/paper/2204.09868"},"outbound":[],"paper":{"arxiv_id":"2204.09868","last_updated":"2022-04-21T03:53:19Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T04:18:21.689354Z","submitted_at":"2022-04-21T03:53:19Z","title":"Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2204.09868."}