{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:B2XVCL6KLEOJIXE2V4LGJ6XAND","short_pith_number":"pith:B2XVCL6K","canonical_record":{"source":{"id":"2210.09043","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-14T01:51:33Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9a41326480dd51b6214bb852b7388d125c9c5a2cc648ac0da4335b079dfd069c","abstract_canon_sha256":"3dc6ec3abf58b79745205503c29bcbe8275cae7c967fc283af8bb564909e5787"},"schema_version":"1.0"},"canonical_sha256":"0eaf512fca591c945c9aaf1664fae068f3f11e17d9d032150a1e2b958904e0db","source":{"kind":"arxiv","id":"2210.09043","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.09043","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"arxiv_version","alias_value":"2210.09043v2","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.09043","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"pith_short_12","alias_value":"B2XVCL6KLEOJ","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"pith_short_16","alias_value":"B2XVCL6KLEOJIXE2","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"pith_short_8","alias_value":"B2XVCL6K","created_at":"2026-07-05T06:41:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:B2XVCL6KLEOJIXE2V4LGJ6XAND","target":"record","payload":{"canonical_record":{"source":{"id":"2210.09043","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-14T01:51:33Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9a41326480dd51b6214bb852b7388d125c9c5a2cc648ac0da4335b079dfd069c","abstract_canon_sha256":"3dc6ec3abf58b79745205503c29bcbe8275cae7c967fc283af8bb564909e5787"},"schema_version":"1.0"},"canonical_sha256":"0eaf512fca591c945c9aaf1664fae068f3f11e17d9d032150a1e2b958904e0db","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:41:45.529777Z","signature_b64":"1604x0YoT4RzkQw3m1qTXTJQFPsqISDwSTdPjfymRZiPdiu/dY+9V0kJ/uThwkLhGxKZgXCqJtwY/WVHPa7ZDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0eaf512fca591c945c9aaf1664fae068f3f11e17d9d032150a1e2b958904e0db","last_reissued_at":"2026-07-05T06:41:45.529279Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:41:45.529279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.09043","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":"2026-07-05T06:41:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BLff0yEkiZCSqpU/4Pm/sptQKQJWLAka5jkb7IjWP51fyhIh6eSNK3b1OBdLtUoOdM6Uef87YhY8lqqqM5ucDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T21:30:04.415012Z"},"content_sha256":"82abad89a795aaffa9d967d5f09d36eb71d32cd452d09019ed71e71d6d21750d","schema_version":"1.0","event_id":"sha256:82abad89a795aaffa9d967d5f09d36eb71d32cd452d09019ed71e71d6d21750d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:B2XVCL6KLEOJIXE2V4LGJ6XAND","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ST-former for short-term passenger flow prediction during COVID-19 in urban rail transit system","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Chengcheng Wang, Jinlei Zhang, Lixing Yang, Shuxin Zhang, Ziyou Gao","submitted_at":"2022-10-14T01:51:33Z","abstract_excerpt":"Accurate passenger flow prediction of urban rail transit is essential for improving the performance of intelligent transportation systems, especially during the epidemic. How to dynamically model the complex spatiotemporal dependencies of passenger flow is the main issue in achieving accurate passenger flow prediction during the epidemic. To solve this issue, this paper proposes a brand-new transformer-based architecture called STformer under the encoder-decoder framework specifically for COVID-19. Concretely, we develop a modified self-attention mechanism named Causal-Convolution ProbSparse S"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.09043","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/2210.09043/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":"2026-07-05T06:41:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RDhxlvfFDnYPNIkVsoXtptOZ2Hbk3T3YUTR91GdMvYB+Tx9fng12m/Md6Fm/g0JZ9ri6gTkqxgA3sv/UPyFXBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T21:30:04.415409Z"},"content_sha256":"38fa209d76d403a183a253a1272d8ba16d471433fb6017c073305305990bffc3","schema_version":"1.0","event_id":"sha256:38fa209d76d403a183a253a1272d8ba16d471433fb6017c073305305990bffc3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B2XVCL6KLEOJIXE2V4LGJ6XAND/bundle.json","state_url":"https://pith.science/pith/B2XVCL6KLEOJIXE2V4LGJ6XAND/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B2XVCL6KLEOJIXE2V4LGJ6XAND/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":"2026-07-24T21:30:04Z","links":{"resolver":"https://pith.science/pith/B2XVCL6KLEOJIXE2V4LGJ6XAND","bundle":"https://pith.science/pith/B2XVCL6KLEOJIXE2V4LGJ6XAND/bundle.json","state":"https://pith.science/pith/B2XVCL6KLEOJIXE2V4LGJ6XAND/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B2XVCL6KLEOJIXE2V4LGJ6XAND/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:B2XVCL6KLEOJIXE2V4LGJ6XAND","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":"3dc6ec3abf58b79745205503c29bcbe8275cae7c967fc283af8bb564909e5787","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-14T01:51:33Z","title_canon_sha256":"9a41326480dd51b6214bb852b7388d125c9c5a2cc648ac0da4335b079dfd069c"},"schema_version":"1.0","source":{"id":"2210.09043","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.09043","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"arxiv_version","alias_value":"2210.09043v2","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.09043","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"pith_short_12","alias_value":"B2XVCL6KLEOJ","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"pith_short_16","alias_value":"B2XVCL6KLEOJIXE2","created_at":"2026-07-05T06:41:45Z"},{"alias_kind":"pith_short_8","alias_value":"B2XVCL6K","created_at":"2026-07-05T06:41:45Z"}],"graph_snapshots":[{"event_id":"sha256:38fa209d76d403a183a253a1272d8ba16d471433fb6017c073305305990bffc3","target":"graph","created_at":"2026-07-05T06:41:45Z","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/2210.09043/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate passenger flow prediction of urban rail transit is essential for improving the performance of intelligent transportation systems, especially during the epidemic. How to dynamically model the complex spatiotemporal dependencies of passenger flow is the main issue in achieving accurate passenger flow prediction during the epidemic. To solve this issue, this paper proposes a brand-new transformer-based architecture called STformer under the encoder-decoder framework specifically for COVID-19. Concretely, we develop a modified self-attention mechanism named Causal-Convolution ProbSparse S","authors_text":"Chengcheng Wang, Jinlei Zhang, Lixing Yang, Shuxin Zhang, Ziyou Gao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-14T01:51:33Z","title":"ST-former for short-term passenger flow prediction during COVID-19 in urban rail transit system"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.09043","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":"sha256:82abad89a795aaffa9d967d5f09d36eb71d32cd452d09019ed71e71d6d21750d","target":"record","created_at":"2026-07-05T06:41:45Z","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":"3dc6ec3abf58b79745205503c29bcbe8275cae7c967fc283af8bb564909e5787","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-14T01:51:33Z","title_canon_sha256":"9a41326480dd51b6214bb852b7388d125c9c5a2cc648ac0da4335b079dfd069c"},"schema_version":"1.0","source":{"id":"2210.09043","kind":"arxiv","version":2}},"canonical_sha256":"0eaf512fca591c945c9aaf1664fae068f3f11e17d9d032150a1e2b958904e0db","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0eaf512fca591c945c9aaf1664fae068f3f11e17d9d032150a1e2b958904e0db","first_computed_at":"2026-07-05T06:41:45.529279Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:41:45.529279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1604x0YoT4RzkQw3m1qTXTJQFPsqISDwSTdPjfymRZiPdiu/dY+9V0kJ/uThwkLhGxKZgXCqJtwY/WVHPa7ZDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:41:45.529777Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.09043","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82abad89a795aaffa9d967d5f09d36eb71d32cd452d09019ed71e71d6d21750d","sha256:38fa209d76d403a183a253a1272d8ba16d471433fb6017c073305305990bffc3"],"state_sha256":"a25181b2b1da360115600d8d33272df05c11a3b18877446f8567e9864694a3b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EjKJbqLEG5+roPIxfdIKesjxzwLdipaCjhLbmWnSQQo3DyL5Jvo64D6wXFByVjk5mBYT1kjLGfPOc7KM0I0OBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-24T21:30:04.417795Z","bundle_sha256":"400d544942ee76a1cc718b8962b3085e9614623ed9891b5d4dc3b7e05f0db195"}}