{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LSK3ZBE6H2DPHCTCV2UMRCA3SV","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":"52ee9170397fa6d57343f8bbbc79ffc7a6bb0b5307e1dea291bb7a740a90a2f7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-27T17:19:26Z","title_canon_sha256":"a9a310ad3129311b4127d86804737c3c3dee78247652bf86746c06c2938b4b02"},"schema_version":"1.0","source":{"id":"2304.14343","kind":"arxiv","version":7}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.14343","created_at":"2026-07-05T07:53:08Z"},{"alias_kind":"arxiv_version","alias_value":"2304.14343v7","created_at":"2026-07-05T07:53:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.14343","created_at":"2026-07-05T07:53:08Z"},{"alias_kind":"pith_short_12","alias_value":"LSK3ZBE6H2DP","created_at":"2026-07-05T07:53:08Z"},{"alias_kind":"pith_short_16","alias_value":"LSK3ZBE6H2DPHCTC","created_at":"2026-07-05T07:53:08Z"},{"alias_kind":"pith_short_8","alias_value":"LSK3ZBE6","created_at":"2026-07-05T07:53:08Z"}],"graph_snapshots":[{"event_id":"sha256:13c957525bb3960e8ea6ad26e19b5144d45935d5cf2278f49f30628acdb888d7","target":"graph","created_at":"2026-07-05T07:53:08Z","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/2304.14343/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As deep learning technology advances and more urban spatial-temporal data accumulates, an increasing number of deep learning models are being proposed to solve urban spatial-temporal prediction problems. However, there are limitations in the existing field, including open-source data being in various formats and difficult to use, few papers making their code and data openly available, and open-source models often using different frameworks and platforms, making comparisons challenging. A standardized framework is urgently needed to implement and evaluate these methods. To address these issues,","authors_text":"Chengkai Han, Jiawei Jiang, Jingyuan Wang, Wayne Xin Zhao, Wenjun Jiang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-27T17:19:26Z","title":"LibCity: A Unified Library Towards Efficient and Comprehensive Urban Spatial-Temporal Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.14343","kind":"arxiv","version":7},"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":"sha256:38cee9f68b050bb3548f19d9bf8c3704f81a5e6fd661fc31c8e6be0d096b9246","target":"record","created_at":"2026-07-05T07:53:08Z","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":"52ee9170397fa6d57343f8bbbc79ffc7a6bb0b5307e1dea291bb7a740a90a2f7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-27T17:19:26Z","title_canon_sha256":"a9a310ad3129311b4127d86804737c3c3dee78247652bf86746c06c2938b4b02"},"schema_version":"1.0","source":{"id":"2304.14343","kind":"arxiv","version":7}},"canonical_sha256":"5c95bc849e3e86f38a62aea8c8881b9578c5d04149f85931c0e16c0493dc51c4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5c95bc849e3e86f38a62aea8c8881b9578c5d04149f85931c0e16c0493dc51c4","first_computed_at":"2026-07-05T07:53:08.202816Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:53:08.202816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z8ivsCHtrObp/VcRS+Zld6EaTaXBR+xtdVgXrmpuJTd6zpdksyXfhMM6FpKPafRrw8dP1ZLAkNAfS/m/THstDw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:53:08.203257Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.14343","source_kind":"arxiv","source_version":7}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:38cee9f68b050bb3548f19d9bf8c3704f81a5e6fd661fc31c8e6be0d096b9246","sha256:13c957525bb3960e8ea6ad26e19b5144d45935d5cf2278f49f30628acdb888d7"],"state_sha256":"f1d1eefc6c55c7cc9f502de56c7cb3a1774047ed13704bf17a36c1b0e841571e"}