{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:4FQKMP74RTTPKIFDBEG5ZZKVQV","short_pith_number":"pith:4FQKMP74","schema_version":"1.0","canonical_sha256":"e160a63ffc8ce6f520a3090ddce555854dac1201d42afbd61a7c853d02d095a9","source":{"kind":"arxiv","id":"2403.10887","version":1},"attestation_state":"computed","paper":{"title":"LuoJiaHOG: A Hierarchy Oriented Geo-aware Image Caption Dataset for Remote Sensing Image-Text Retrival","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingnan Yang, Jiaju Kang, Jianya Gong, Mi Zhang, Yuanxin Zhao, Zhan Zhang","submitted_at":"2024-03-16T10:46:14Z","abstract_excerpt":"Image-text retrieval (ITR) plays a significant role in making informed decisions for various remote sensing (RS) applications. Nonetheless, creating ITR datasets containing vision and language modalities not only requires significant geo-spatial sampling area but also varing categories and detailed descriptions. To this end, we introduce an image caption dataset LuojiaHOG, which is geospatial-aware, label-extension-friendly and comprehensive-captioned. LuojiaHOG involves the hierarchical spatial sampling, extensible classification system to Open Geospatial Consortium (OGC) standards, and detai"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2403.10887","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-16T10:46:14Z","cross_cats_sorted":[],"title_canon_sha256":"50e1b869026f6c57d1ffdffa322d5463e48ace1770fde1fa508f7b785999670d","abstract_canon_sha256":"aba952ccc417ab2e03d7ec17d2d0699df0a169e38d008fa481528adc12ca705f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:57:08.605168Z","signature_b64":"colsOJffFH5SC/rojFaHKvtn6bpec3QRhebNLcoUX1VK0JyA38EQy3d6rK9SPr82TkH2VbEF3jSLS7XJWkBYBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e160a63ffc8ce6f520a3090ddce555854dac1201d42afbd61a7c853d02d095a9","last_reissued_at":"2026-07-05T07:57:08.604744Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:57:08.604744Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LuoJiaHOG: A Hierarchy Oriented Geo-aware Image Caption Dataset for Remote Sensing Image-Text Retrival","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingnan Yang, Jiaju Kang, Jianya Gong, Mi Zhang, Yuanxin Zhao, Zhan Zhang","submitted_at":"2024-03-16T10:46:14Z","abstract_excerpt":"Image-text retrieval (ITR) plays a significant role in making informed decisions for various remote sensing (RS) applications. Nonetheless, creating ITR datasets containing vision and language modalities not only requires significant geo-spatial sampling area but also varing categories and detailed descriptions. To this end, we introduce an image caption dataset LuojiaHOG, which is geospatial-aware, label-extension-friendly and comprehensive-captioned. LuojiaHOG involves the hierarchical spatial sampling, extensible classification system to Open Geospatial Consortium (OGC) standards, and detai"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.10887","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2403.10887/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2403.10887","created_at":"2026-07-05T07:57:08.604802+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.10887v1","created_at":"2026-07-05T07:57:08.604802+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.10887","created_at":"2026-07-05T07:57:08.604802+00:00"},{"alias_kind":"pith_short_12","alias_value":"4FQKMP74RTTP","created_at":"2026-07-05T07:57:08.604802+00:00"},{"alias_kind":"pith_short_16","alias_value":"4FQKMP74RTTPKIFD","created_at":"2026-07-05T07:57:08.604802+00:00"},{"alias_kind":"pith_short_8","alias_value":"4FQKMP74","created_at":"2026-07-05T07:57:08.604802+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV","json":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV.json","graph_json":"https://pith.science/api/pith-number/4FQKMP74RTTPKIFDBEG5ZZKVQV/graph.json","events_json":"https://pith.science/api/pith-number/4FQKMP74RTTPKIFDBEG5ZZKVQV/events.json","paper":"https://pith.science/paper/4FQKMP74"},"agent_actions":{"view_html":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV","download_json":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV.json","view_paper":"https://pith.science/paper/4FQKMP74","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.10887&json=true","fetch_graph":"https://pith.science/api/pith-number/4FQKMP74RTTPKIFDBEG5ZZKVQV/graph.json","fetch_events":"https://pith.science/api/pith-number/4FQKMP74RTTPKIFDBEG5ZZKVQV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV/action/storage_attestation","attest_author":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV/action/author_attestation","sign_citation":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV/action/citation_signature","submit_replication":"https://pith.science/pith/4FQKMP74RTTPKIFDBEG5ZZKVQV/action/replication_record"}},"created_at":"2026-07-05T07:57:08.604802+00:00","updated_at":"2026-07-05T07:57:08.604802+00:00"}