{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:7YUBIQ6WRAOW2E2RN7MIYX3U4Y","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":"64bf6974bc7496fe3a83c4507c02808f3971b5e3678f2148bd78a26ab84e9d69","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-03T11:26:09Z","title_canon_sha256":"9e25ea3ad6e5688833217a21ce0204d825e40c27c433ab197fe8acd8f03e6058"},"schema_version":"1.0","source":{"id":"2210.00828","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.00828","created_at":"2026-07-05T05:02:48Z"},{"alias_kind":"arxiv_version","alias_value":"2210.00828v1","created_at":"2026-07-05T05:02:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.00828","created_at":"2026-07-05T05:02:48Z"},{"alias_kind":"pith_short_12","alias_value":"7YUBIQ6WRAOW","created_at":"2026-07-05T05:02:48Z"},{"alias_kind":"pith_short_16","alias_value":"7YUBIQ6WRAOW2E2R","created_at":"2026-07-05T05:02:48Z"},{"alias_kind":"pith_short_8","alias_value":"7YUBIQ6W","created_at":"2026-07-05T05:02:48Z"}],"graph_snapshots":[{"event_id":"sha256:4e17976fb7d4e6b92f8258b3393e78476696e05bfe8aaae88c988ab8e07a6710","target":"graph","created_at":"2026-07-05T05:02:48Z","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/2210.00828/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurately predicting road networks from satellite images requires a global understanding of the network topology. We propose to capture such high-level information by introducing a graph-based framework that simulates the addition of sequences of graph edges using a reinforcement learning (RL) approach. In particular, given a partially generated graph associated with a satellite image, an RL agent nominates modifications that maximize a cumulative reward. As opposed to standard supervised techniques that tend to be more restricted to commonly used surrogate losses, these rewards can be based ","authors_text":"Aurelien Lucchi, Sotiris Anagnostidis, Thomas Hofmann","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-03T11:26:09Z","title":"Mastering Spatial Graph Prediction of Road Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.00828","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":"sha256:8f26fbcbb2b0a1e0b62418abef491f74ebe676487aeb65e3625529c09f4d31c5","target":"record","created_at":"2026-07-05T05:02:48Z","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":"64bf6974bc7496fe3a83c4507c02808f3971b5e3678f2148bd78a26ab84e9d69","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-03T11:26:09Z","title_canon_sha256":"9e25ea3ad6e5688833217a21ce0204d825e40c27c433ab197fe8acd8f03e6058"},"schema_version":"1.0","source":{"id":"2210.00828","kind":"arxiv","version":1}},"canonical_sha256":"fe281443d6881d6d13516fd88c5f74e604af5f08c5c37ec308d13af959a0abae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe281443d6881d6d13516fd88c5f74e604af5f08c5c37ec308d13af959a0abae","first_computed_at":"2026-07-05T05:02:48.311683Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:02:48.311683Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A8y8Qvm4/+nmcxzp9t6Eo4MsW8Plq/l/+8VCUpRTtLPmZTYW4nWrIgW3rRzW8+/d8GVHu0pHW6BC7iGRvzcVDA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:02:48.312097Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.00828","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8f26fbcbb2b0a1e0b62418abef491f74ebe676487aeb65e3625529c09f4d31c5","sha256:4e17976fb7d4e6b92f8258b3393e78476696e05bfe8aaae88c988ab8e07a6710"],"state_sha256":"ef9516064cee0243c102e1457b1660570c79e62f7be80979874bd0f8daed922f"}