{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7PHGZIQMWJR2R2CEZXBX3DMNOU","short_pith_number":"pith:7PHGZIQM","canonical_record":{"source":{"id":"2403.16051","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-24T07:36:38Z","cross_cats_sorted":[],"title_canon_sha256":"0ea2e596bb29084544471aa91eeefb1372da5037217ffe8aa33a1e8447d357dc","abstract_canon_sha256":"4e884ee2bfc196d2412db746b7cc02d8d91555c309facab5390a0de844a63cdb"},"schema_version":"1.0"},"canonical_sha256":"fbce6ca20cb263a8e844cdc37d8d8d752e302eff73acc441d015d1c43125f7e2","source":{"kind":"arxiv","id":"2403.16051","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.16051","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"arxiv_version","alias_value":"2403.16051v3","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.16051","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"pith_short_12","alias_value":"7PHGZIQMWJR2","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"pith_short_16","alias_value":"7PHGZIQMWJR2R2CE","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"pith_short_8","alias_value":"7PHGZIQM","created_at":"2026-07-05T08:07:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7PHGZIQMWJR2R2CEZXBX3DMNOU","target":"record","payload":{"canonical_record":{"source":{"id":"2403.16051","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-24T07:36:38Z","cross_cats_sorted":[],"title_canon_sha256":"0ea2e596bb29084544471aa91eeefb1372da5037217ffe8aa33a1e8447d357dc","abstract_canon_sha256":"4e884ee2bfc196d2412db746b7cc02d8d91555c309facab5390a0de844a63cdb"},"schema_version":"1.0"},"canonical_sha256":"fbce6ca20cb263a8e844cdc37d8d8d752e302eff73acc441d015d1c43125f7e2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:07:34.865845Z","signature_b64":"P//plB7tZmEQeQindU3sTb6IOOWmbctRTMGubOuwmdTRQzEbx+Kj+Akp0PfZOM31LrTxRx8dBvvho9xc4qO+DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fbce6ca20cb263a8e844cdc37d8d8d752e302eff73acc441d015d1c43125f7e2","last_reissued_at":"2026-07-05T08:07:34.861669Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:07:34.861669Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.16051","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:07:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"98/E1/izhnpeWpl8+4ZIz2oOOnaHLy5dOAfSy1njifUaIbYSkjqoxce7stBnVPz9WlbNYa5bTpI0L007MWkgDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:26:49.995409Z"},"content_sha256":"ed6acdbf1da18a706f188cd34cb2374f508a7f3ab5bf3e915d6e7f83794d7e1b","schema_version":"1.0","event_id":"sha256:ed6acdbf1da18a706f188cd34cb2374f508a7f3ab5bf3e915d6e7f83794d7e1b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7PHGZIQMWJR2R2CEZXBX3DMNOU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Segment Anything Model for Road Network Graph Extraction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cindy Le, Congrui Hetang, Haoru Xue, Tianwei Yue, Wenping Wang, Yihui He","submitted_at":"2024-03-24T07:36:38Z","abstract_excerpt":"We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) for extracting large-scale, vectorized road network graphs from satellite imagery. To predict graph geometry, we formulate it as a dense semantic segmentation task, leveraging the inherent strengths of SAM. The image encoder of SAM is fine-tuned to produce probability masks for roads and intersections, from which the graph vertices are extracted via simple non-maximum suppression. To predict graph topology, we designed a lightweight transformer-based graph neural network, which leverages the SAM image embeddings to estimate"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.16051","kind":"arxiv","version":3},"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/2403.16051/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:07:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qp9j8wApG52IgXb+6UxIK0aicEk8zsL9PpjpUcaeZTZHnJ2tc4sDVhFDDlxYoutBelD0QzF9YTGqXP/XLDeEBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:26:49.995933Z"},"content_sha256":"131dca67188bb90d9cf67e1383026d1da2f2cd60453237a497fb785d71e19ff4","schema_version":"1.0","event_id":"sha256:131dca67188bb90d9cf67e1383026d1da2f2cd60453237a497fb785d71e19ff4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7PHGZIQMWJR2R2CEZXBX3DMNOU/bundle.json","state_url":"https://pith.science/pith/7PHGZIQMWJR2R2CEZXBX3DMNOU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7PHGZIQMWJR2R2CEZXBX3DMNOU/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-06T03:26:49Z","links":{"resolver":"https://pith.science/pith/7PHGZIQMWJR2R2CEZXBX3DMNOU","bundle":"https://pith.science/pith/7PHGZIQMWJR2R2CEZXBX3DMNOU/bundle.json","state":"https://pith.science/pith/7PHGZIQMWJR2R2CEZXBX3DMNOU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7PHGZIQMWJR2R2CEZXBX3DMNOU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7PHGZIQMWJR2R2CEZXBX3DMNOU","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":"4e884ee2bfc196d2412db746b7cc02d8d91555c309facab5390a0de844a63cdb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-24T07:36:38Z","title_canon_sha256":"0ea2e596bb29084544471aa91eeefb1372da5037217ffe8aa33a1e8447d357dc"},"schema_version":"1.0","source":{"id":"2403.16051","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.16051","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"arxiv_version","alias_value":"2403.16051v3","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.16051","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"pith_short_12","alias_value":"7PHGZIQMWJR2","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"pith_short_16","alias_value":"7PHGZIQMWJR2R2CE","created_at":"2026-07-05T08:07:34Z"},{"alias_kind":"pith_short_8","alias_value":"7PHGZIQM","created_at":"2026-07-05T08:07:34Z"}],"graph_snapshots":[{"event_id":"sha256:131dca67188bb90d9cf67e1383026d1da2f2cd60453237a497fb785d71e19ff4","target":"graph","created_at":"2026-07-05T08:07:34Z","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/2403.16051/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) for extracting large-scale, vectorized road network graphs from satellite imagery. To predict graph geometry, we formulate it as a dense semantic segmentation task, leveraging the inherent strengths of SAM. The image encoder of SAM is fine-tuned to produce probability masks for roads and intersections, from which the graph vertices are extracted via simple non-maximum suppression. To predict graph topology, we designed a lightweight transformer-based graph neural network, which leverages the SAM image embeddings to estimate","authors_text":"Cindy Le, Congrui Hetang, Haoru Xue, Tianwei Yue, Wenping Wang, Yihui He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-24T07:36:38Z","title":"Segment Anything Model for Road Network Graph Extraction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.16051","kind":"arxiv","version":3},"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:ed6acdbf1da18a706f188cd34cb2374f508a7f3ab5bf3e915d6e7f83794d7e1b","target":"record","created_at":"2026-07-05T08:07:34Z","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":"4e884ee2bfc196d2412db746b7cc02d8d91555c309facab5390a0de844a63cdb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-24T07:36:38Z","title_canon_sha256":"0ea2e596bb29084544471aa91eeefb1372da5037217ffe8aa33a1e8447d357dc"},"schema_version":"1.0","source":{"id":"2403.16051","kind":"arxiv","version":3}},"canonical_sha256":"fbce6ca20cb263a8e844cdc37d8d8d752e302eff73acc441d015d1c43125f7e2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fbce6ca20cb263a8e844cdc37d8d8d752e302eff73acc441d015d1c43125f7e2","first_computed_at":"2026-07-05T08:07:34.861669Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:07:34.861669Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P//plB7tZmEQeQindU3sTb6IOOWmbctRTMGubOuwmdTRQzEbx+Kj+Akp0PfZOM31LrTxRx8dBvvho9xc4qO+DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:07:34.865845Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.16051","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ed6acdbf1da18a706f188cd34cb2374f508a7f3ab5bf3e915d6e7f83794d7e1b","sha256:131dca67188bb90d9cf67e1383026d1da2f2cd60453237a497fb785d71e19ff4"],"state_sha256":"e4a73a7231c4a5eb33e2374a95e6f7d5547a976fcb90998b468efd41651d05ce"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TTAvde+nVt4/xEbOsVL5/xmzK+XlVc1B1Mrf3o8Mszhjzkph7cR/fUxIzmamejNUiA0L8Lt7yc+4byZ6q4imCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T03:26:49.999425Z","bundle_sha256":"42cdcb81670fcc71ca647b77a9bbbcd55993429c2a7a1086efc646044d5b2169"}}