{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:AXZW65UXROGSAKTMLQX5OFKBXO","short_pith_number":"pith:AXZW65UX","canonical_record":{"source":{"id":"2504.08061","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-10T18:32:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"88509a83db445bce709403733c55725b1edcf0b555e0a1281c1dd1f8020d22b4","abstract_canon_sha256":"baef4a280333f4bfb1f6b1bcc70456db80d9f93c8086ec9acc6a2b93e238bb84"},"schema_version":"1.0"},"canonical_sha256":"05f36f76978b8d202a6c5c2fd71541bb8e562babf0f7dc83ed8b1368f762b093","source":{"kind":"arxiv","id":"2504.08061","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.08061","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"arxiv_version","alias_value":"2504.08061v2","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.08061","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"pith_short_12","alias_value":"AXZW65UXROGS","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"pith_short_16","alias_value":"AXZW65UXROGSAKTM","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"pith_short_8","alias_value":"AXZW65UX","created_at":"2026-06-23T02:13:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:AXZW65UXROGSAKTMLQX5OFKBXO","target":"record","payload":{"canonical_record":{"source":{"id":"2504.08061","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-10T18:32:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"88509a83db445bce709403733c55725b1edcf0b555e0a1281c1dd1f8020d22b4","abstract_canon_sha256":"baef4a280333f4bfb1f6b1bcc70456db80d9f93c8086ec9acc6a2b93e238bb84"},"schema_version":"1.0"},"canonical_sha256":"05f36f76978b8d202a6c5c2fd71541bb8e562babf0f7dc83ed8b1368f762b093","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T02:13:14.941747Z","signature_b64":"HEjKm4WalQ6cn19IG92no+deX9GeYOAgu+wQX+bBi95U0iJZznkNl9O8mfd9tXkiXdwlO4wGFPuoOp6dKq1ECw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"05f36f76978b8d202a6c5c2fd71541bb8e562babf0f7dc83ed8b1368f762b093","last_reissued_at":"2026-06-23T02:13:14.941167Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T02:13:14.941167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.08061","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-23T02:13:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H/UI/7y4GjbRd0Qsr53evkggDJrR7i1cs6SgCufBlSKWmQzep1TSllTawnYExOZ2jTMHkiMHeg7W4fDxkDyJAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:41:50.805614Z"},"content_sha256":"47f75d919bb27aab52af883eb8bd738af3c3297644c17a3b2ab83ade637899e4","schema_version":"1.0","event_id":"sha256:47f75d919bb27aab52af883eb8bd738af3c3297644c17a3b2ab83ade637899e4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:AXZW65UXROGSAKTMLQX5OFKBXO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Traffic State Prediction With Dynamic Joint Spatio-Temporal Relation Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Juncai Zhang, Kai Hu, Zhengming Chen, Zhidan Zhao, Zhifeng Hao","submitted_at":"2025-04-10T18:32:56Z","abstract_excerpt":"Traffic prediction is difficult due to the complex interplay of temporal evolution, spatial interactions, and delayed spatio-temporal propagation over road networks. Existing methods either model spatial and temporal dependencies separately or employ unified spatio-temporal structures, but they often insufficiently characterize how neighboring sensors at historical timestamps influence a target node, while complex joint models may incur high computation. This paper proposes STEI-PCN, an efficient pure convolutional network based on spatio-temporal encoding and relation inference. It first buil"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.08061","kind":"arxiv","version":2},"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/2504.08061/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":"2026-06-23T02:13:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UP5oHo05/A0ZnAccLKaHvfF+ENy9nOI5Jot5yTgjj9iMRE38zrpGmpXBHyrIfI0JeeoDt7CpXQ7TH43s/yQTCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:41:50.806020Z"},"content_sha256":"39dc5e9b482b2bf4a5e7cb0f6750575b10a0b91ae8daaa42c584b067c2ba48b8","schema_version":"1.0","event_id":"sha256:39dc5e9b482b2bf4a5e7cb0f6750575b10a0b91ae8daaa42c584b067c2ba48b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AXZW65UXROGSAKTMLQX5OFKBXO/bundle.json","state_url":"https://pith.science/pith/AXZW65UXROGSAKTMLQX5OFKBXO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AXZW65UXROGSAKTMLQX5OFKBXO/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":"2026-07-09T05:41:50Z","links":{"resolver":"https://pith.science/pith/AXZW65UXROGSAKTMLQX5OFKBXO","bundle":"https://pith.science/pith/AXZW65UXROGSAKTMLQX5OFKBXO/bundle.json","state":"https://pith.science/pith/AXZW65UXROGSAKTMLQX5OFKBXO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AXZW65UXROGSAKTMLQX5OFKBXO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:AXZW65UXROGSAKTMLQX5OFKBXO","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":"baef4a280333f4bfb1f6b1bcc70456db80d9f93c8086ec9acc6a2b93e238bb84","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-10T18:32:56Z","title_canon_sha256":"88509a83db445bce709403733c55725b1edcf0b555e0a1281c1dd1f8020d22b4"},"schema_version":"1.0","source":{"id":"2504.08061","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.08061","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"arxiv_version","alias_value":"2504.08061v2","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.08061","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"pith_short_12","alias_value":"AXZW65UXROGS","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"pith_short_16","alias_value":"AXZW65UXROGSAKTM","created_at":"2026-06-23T02:13:14Z"},{"alias_kind":"pith_short_8","alias_value":"AXZW65UX","created_at":"2026-06-23T02:13:14Z"}],"graph_snapshots":[{"event_id":"sha256:39dc5e9b482b2bf4a5e7cb0f6750575b10a0b91ae8daaa42c584b067c2ba48b8","target":"graph","created_at":"2026-06-23T02:13:14Z","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/2504.08061/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traffic prediction is difficult due to the complex interplay of temporal evolution, spatial interactions, and delayed spatio-temporal propagation over road networks. Existing methods either model spatial and temporal dependencies separately or employ unified spatio-temporal structures, but they often insufficiently characterize how neighboring sensors at historical timestamps influence a target node, while complex joint models may incur high computation. This paper proposes STEI-PCN, an efficient pure convolutional network based on spatio-temporal encoding and relation inference. It first buil","authors_text":"Juncai Zhang, Kai Hu, Zhengming Chen, Zhidan Zhao, Zhifeng Hao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-10T18:32:56Z","title":"Efficient Traffic State Prediction With Dynamic Joint Spatio-Temporal Relation Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.08061","kind":"arxiv","version":2},"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":"sha256:47f75d919bb27aab52af883eb8bd738af3c3297644c17a3b2ab83ade637899e4","target":"record","created_at":"2026-06-23T02:13:14Z","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":"baef4a280333f4bfb1f6b1bcc70456db80d9f93c8086ec9acc6a2b93e238bb84","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-10T18:32:56Z","title_canon_sha256":"88509a83db445bce709403733c55725b1edcf0b555e0a1281c1dd1f8020d22b4"},"schema_version":"1.0","source":{"id":"2504.08061","kind":"arxiv","version":2}},"canonical_sha256":"05f36f76978b8d202a6c5c2fd71541bb8e562babf0f7dc83ed8b1368f762b093","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"05f36f76978b8d202a6c5c2fd71541bb8e562babf0f7dc83ed8b1368f762b093","first_computed_at":"2026-06-23T02:13:14.941167Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T02:13:14.941167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HEjKm4WalQ6cn19IG92no+deX9GeYOAgu+wQX+bBi95U0iJZznkNl9O8mfd9tXkiXdwlO4wGFPuoOp6dKq1ECw==","signature_status":"signed_v1","signed_at":"2026-06-23T02:13:14.941747Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.08061","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:47f75d919bb27aab52af883eb8bd738af3c3297644c17a3b2ab83ade637899e4","sha256:39dc5e9b482b2bf4a5e7cb0f6750575b10a0b91ae8daaa42c584b067c2ba48b8"],"state_sha256":"e63b36ae1a181adf63bfdb7b23f747bd079117d86b5b8954b101e852f930253d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ENkTEyvHQ67pQ4h+0HsZ7qRPNGctcMTZN729JZ+h/Ey7cu4VrkvVWnlnhBYR5hCDW2a9IgjY9WDzH2yHZYRCCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T05:41:50.808199Z","bundle_sha256":"9398906bb9b5e9126127b2634c1de9806b36021c8314cfbc56b0e6f45b755c45"}}