{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4U475PXSJQCL4GFGJ3SCSEEGAH","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"80c283d40ba580a9812f0bfb2550a32423024c0ffb8c5fa82d48dfa9e0527439","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-22T10:14:18Z","title_canon_sha256":"38538731e1628b80cdb0b8a44ffe0f399ae110d6f29fdbd7a551c8da9ac195c6"},"schema_version":"1.0","source":{"id":"2508.16272","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.16272","created_at":"2026-07-05T11:57:45Z"},{"alias_kind":"arxiv_version","alias_value":"2508.16272v1","created_at":"2026-07-05T11:57:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.16272","created_at":"2026-07-05T11:57:45Z"},{"alias_kind":"pith_short_12","alias_value":"4U475PXSJQCL","created_at":"2026-07-05T11:57:45Z"},{"alias_kind":"pith_short_16","alias_value":"4U475PXSJQCL4GFG","created_at":"2026-07-05T11:57:45Z"},{"alias_kind":"pith_short_8","alias_value":"4U475PXS","created_at":"2026-07-05T11:57:45Z"}],"graph_snapshots":[{"event_id":"sha256:fb816b2d3b1b34784f76022d4d6e28c7ce99568ed84d40b7482cf0435cb34ee8","target":"graph","created_at":"2026-07-05T11:57:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2508.16272/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the enhancement of remote sensing image resolution and the rapid advancement of deep learning, land cover mapping is transitioning from pixel-level segmentation to object-based vector modeling. This shift demands more from deep learning models, requiring precise object boundaries and topological consistency. However, existing datasets face three main challenges: limited class annotations, small data scale, and lack of spatial structural information. To overcome these issues, we introduce IRSAMap, the first global remote sensing dataset for large-scale, high-resolution, multi-feature land ","authors_text":"Anzhi Yue, Chenhao Wang, Diyou Liu, Jiansheng Chen, Jingbo Chen, Kai Li, Kaiyu Li, Ligao Deng, Xian Sun, Yu Meng, Yupeng Deng, Zhihao Xi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-22T10:14:18Z","title":"IRSAMap:Towards Large-Scale, High-Resolution Land Cover Map Vectorization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.16272","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4583b5db845adbba12b2ffc9dfb382e4fa32e3bcbd19ea5046e9dc69ac089dc8","target":"record","created_at":"2026-07-05T11:57:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"80c283d40ba580a9812f0bfb2550a32423024c0ffb8c5fa82d48dfa9e0527439","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-22T10:14:18Z","title_canon_sha256":"38538731e1628b80cdb0b8a44ffe0f399ae110d6f29fdbd7a551c8da9ac195c6"},"schema_version":"1.0","source":{"id":"2508.16272","kind":"arxiv","version":1}},"canonical_sha256":"e539febef24c04be18a64ee429108601e73208cbbeaaeb5dcab3a8f09314460a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e539febef24c04be18a64ee429108601e73208cbbeaaeb5dcab3a8f09314460a","first_computed_at":"2026-07-05T11:57:45.082675Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:57:45.082675Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jmmdESWKTJDe8axy5+DjNU6Ncx/4llVmzfMeoY/cP22PyC0JRJdUvw+ptkv3BNLjL7iXIkol8grFapRooSkyBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:57:45.083088Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.16272","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4583b5db845adbba12b2ffc9dfb382e4fa32e3bcbd19ea5046e9dc69ac089dc8","sha256:fb816b2d3b1b34784f76022d4d6e28c7ce99568ed84d40b7482cf0435cb34ee8"],"state_sha256":"8021bee441be703438ae824de749cf5f4995d28dee646ddae1b4fe6b1896cce0"}