{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OBJEAOFAMK324XH6H7LAEVY2XM","short_pith_number":"pith:OBJEAOFA","canonical_record":{"source":{"id":"2412.17373","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T08:14:20Z","cross_cats_sorted":[],"title_canon_sha256":"19965abdd5471d6edbf4f9361b47d920966635437bbccac504ee6d1f9b6dbcb4","abstract_canon_sha256":"e10c70dfa70582add2a1feeef1a373c7c0ffb19da5fc2852047b4acde18fad73"},"schema_version":"1.0"},"canonical_sha256":"70524038a062b7ae5cfe3fd602571abb164654142ac7832658a23441d4e83f84","source":{"kind":"arxiv","id":"2412.17373","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.17373","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"arxiv_version","alias_value":"2412.17373v1","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17373","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_12","alias_value":"OBJEAOFAMK32","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_16","alias_value":"OBJEAOFAMK324XH6","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_8","alias_value":"OBJEAOFA","created_at":"2026-07-05T09:53:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OBJEAOFAMK324XH6H7LAEVY2XM","target":"record","payload":{"canonical_record":{"source":{"id":"2412.17373","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T08:14:20Z","cross_cats_sorted":[],"title_canon_sha256":"19965abdd5471d6edbf4f9361b47d920966635437bbccac504ee6d1f9b6dbcb4","abstract_canon_sha256":"e10c70dfa70582add2a1feeef1a373c7c0ffb19da5fc2852047b4acde18fad73"},"schema_version":"1.0"},"canonical_sha256":"70524038a062b7ae5cfe3fd602571abb164654142ac7832658a23441d4e83f84","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:53:21.612963Z","signature_b64":"zBfvpkHQcw58Vs3ORmDZhCw6RVPhbxBTBk5B1fPot0gLCpOGWYRq7nOZIr/Z+B0RA3lUypEG6NWAPRDLfEHeBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"70524038a062b7ae5cfe3fd602571abb164654142ac7832658a23441d4e83f84","last_reissued_at":"2026-07-05T09:53:21.612521Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:53:21.612521Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.17373","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:53:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tGtcDoRKON1TvTXRQKDBfwlTC563Fnh/i6hlHSeayHDdn1H62GfIRa7SqQKp0bADZFkRTuoTo5cqkH1weViHAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T15:33:44.482535Z"},"content_sha256":"ce797d5c5f18a8d49fde70a5773ac3a7217e5afabfdd5273dd8762afb20829ed","schema_version":"1.0","event_id":"sha256:ce797d5c5f18a8d49fde70a5773ac3a7217e5afabfdd5273dd8762afb20829ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OBJEAOFAMK324XH6H7LAEVY2XM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FRTP: Federating Route Search Records to Enhance Long-term Traffic Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Dizhi Huang, Hangli Ge, Itsuki Matsunaga, Noboru Koshizuka, Xiaojie Yang","submitted_at":"2024-12-23T08:14:20Z","abstract_excerpt":"Accurate traffic prediction, especially predicting traffic conditions several days in advance is essential for intelligent transportation systems (ITS). Such predictions enable mid- and long-term traffic optimization, which is crucial for efficient transportation planning. However, the inclusion of diverse external features, alongside the complexities of spatial relationships and temporal uncertainties, significantly increases the complexity of forecasting models. Additionally, traditional approaches have handled data preprocessing separately from the learning model, leading to inefficiencies "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17373","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/2412.17373/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":"2026-07-05T09:53:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FbzVrHRakvXFWXvLjNs3c4B8MX0b9pT2VuQhlLLBse/astEIK2EbsjYXveoQMKV/13jjQg7POXmOfRtOV7KBAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T15:33:44.483161Z"},"content_sha256":"abb07a315a3ae39623f19265dec9009369564319165bc4ee793351d608bff3ad","schema_version":"1.0","event_id":"sha256:abb07a315a3ae39623f19265dec9009369564319165bc4ee793351d608bff3ad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OBJEAOFAMK324XH6H7LAEVY2XM/bundle.json","state_url":"https://pith.science/pith/OBJEAOFAMK324XH6H7LAEVY2XM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OBJEAOFAMK324XH6H7LAEVY2XM/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":"2026-08-17T15:33:44Z","links":{"resolver":"https://pith.science/pith/OBJEAOFAMK324XH6H7LAEVY2XM","bundle":"https://pith.science/pith/OBJEAOFAMK324XH6H7LAEVY2XM/bundle.json","state":"https://pith.science/pith/OBJEAOFAMK324XH6H7LAEVY2XM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OBJEAOFAMK324XH6H7LAEVY2XM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OBJEAOFAMK324XH6H7LAEVY2XM","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":"e10c70dfa70582add2a1feeef1a373c7c0ffb19da5fc2852047b4acde18fad73","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T08:14:20Z","title_canon_sha256":"19965abdd5471d6edbf4f9361b47d920966635437bbccac504ee6d1f9b6dbcb4"},"schema_version":"1.0","source":{"id":"2412.17373","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.17373","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"arxiv_version","alias_value":"2412.17373v1","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17373","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_12","alias_value":"OBJEAOFAMK32","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_16","alias_value":"OBJEAOFAMK324XH6","created_at":"2026-07-05T09:53:21Z"},{"alias_kind":"pith_short_8","alias_value":"OBJEAOFA","created_at":"2026-07-05T09:53:21Z"}],"graph_snapshots":[{"event_id":"sha256:abb07a315a3ae39623f19265dec9009369564319165bc4ee793351d608bff3ad","target":"graph","created_at":"2026-07-05T09:53:21Z","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/2412.17373/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate traffic prediction, especially predicting traffic conditions several days in advance is essential for intelligent transportation systems (ITS). Such predictions enable mid- and long-term traffic optimization, which is crucial for efficient transportation planning. However, the inclusion of diverse external features, alongside the complexities of spatial relationships and temporal uncertainties, significantly increases the complexity of forecasting models. Additionally, traditional approaches have handled data preprocessing separately from the learning model, leading to inefficiencies ","authors_text":"Dizhi Huang, Hangli Ge, Itsuki Matsunaga, Noboru Koshizuka, Xiaojie Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T08:14:20Z","title":"FRTP: Federating Route Search Records to Enhance Long-term Traffic Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17373","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:ce797d5c5f18a8d49fde70a5773ac3a7217e5afabfdd5273dd8762afb20829ed","target":"record","created_at":"2026-07-05T09:53:21Z","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":"e10c70dfa70582add2a1feeef1a373c7c0ffb19da5fc2852047b4acde18fad73","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-23T08:14:20Z","title_canon_sha256":"19965abdd5471d6edbf4f9361b47d920966635437bbccac504ee6d1f9b6dbcb4"},"schema_version":"1.0","source":{"id":"2412.17373","kind":"arxiv","version":1}},"canonical_sha256":"70524038a062b7ae5cfe3fd602571abb164654142ac7832658a23441d4e83f84","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"70524038a062b7ae5cfe3fd602571abb164654142ac7832658a23441d4e83f84","first_computed_at":"2026-07-05T09:53:21.612521Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:53:21.612521Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zBfvpkHQcw58Vs3ORmDZhCw6RVPhbxBTBk5B1fPot0gLCpOGWYRq7nOZIr/Z+B0RA3lUypEG6NWAPRDLfEHeBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:53:21.612963Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.17373","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ce797d5c5f18a8d49fde70a5773ac3a7217e5afabfdd5273dd8762afb20829ed","sha256:abb07a315a3ae39623f19265dec9009369564319165bc4ee793351d608bff3ad"],"state_sha256":"aef3ff908713144cbe255d30ac63c6e53b83bc1dcb88e0b0b124ae5e6b73eaa3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lUxNQJh+UldYFT5SPXewxGADNiMZmHwrGCzORx7Ii/Rm1D7sNkeuSrf4OwehXbwKdbtMLo5zf7MbYiEBY6n2Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T15:33:44.486852Z","bundle_sha256":"49c2202f74150e317ed1e1efcdf1904de1a9c0af52d917ec2484b4de3621d166"}}