{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:J42VVDUU2ATXB6KFMA5WZRBQB3","short_pith_number":"pith:J42VVDUU","canonical_record":{"source":{"id":"2312.00516","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-01T11:43:49Z","cross_cats_sorted":[],"title_canon_sha256":"5f07ddcc1c8d5642f5b7adc652d746487e4cca103afeb0f1fda0b75aab6c0d62","abstract_canon_sha256":"173b28600773e056a9e7310848a09f12fe16c9f17c1a0cfd0de0100e3a4a4afa"},"schema_version":"1.0"},"canonical_sha256":"4f355a8e94d02770f945603b6cc4300ee12d3c4052701a605984916f98641568","source":{"kind":"arxiv","id":"2312.00516","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.00516","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"arxiv_version","alias_value":"2312.00516v3","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.00516","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"pith_short_12","alias_value":"J42VVDUU2ATX","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"pith_short_16","alias_value":"J42VVDUU2ATXB6KF","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"pith_short_8","alias_value":"J42VVDUU","created_at":"2026-07-05T09:12:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:J42VVDUU2ATXB6KFMA5WZRBQB3","target":"record","payload":{"canonical_record":{"source":{"id":"2312.00516","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-01T11:43:49Z","cross_cats_sorted":[],"title_canon_sha256":"5f07ddcc1c8d5642f5b7adc652d746487e4cca103afeb0f1fda0b75aab6c0d62","abstract_canon_sha256":"173b28600773e056a9e7310848a09f12fe16c9f17c1a0cfd0de0100e3a4a4afa"},"schema_version":"1.0"},"canonical_sha256":"4f355a8e94d02770f945603b6cc4300ee12d3c4052701a605984916f98641568","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:12:57.291595Z","signature_b64":"rK5M4zFZiO2txUcnbj8zWUbtr8DkLbSyrbsLXJa2CMNsKeaxACKlwxBiRT51PYF0cwNvmkRIwtS9tF43gWsrAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f355a8e94d02770f945603b6cc4300ee12d3c4052701a605984916f98641568","last_reissued_at":"2026-07-05T09:12:57.291037Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:12:57.291037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.00516","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":"2026-07-05T09:12:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GZAtwoi5qSy05Lhld+uWpX+3qYxH1lGQJ2R8LHSdy+ZTh8QeMPQgoWwwkeV1Wge7uL08UjhH5cENw2mmB4O+Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T01:06:39.656384Z"},"content_sha256":"31ab1b37f3652aa4bf04afc669fa40a0dc1da1ecf06c6f0f2c0837265c83d9bd","schema_version":"1.0","event_id":"sha256:31ab1b37f3652aa4bf04afc669fa40a0dc1da1ecf06c6f0f2c0837265c83d9bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:J42VVDUU2ATXB6KFMA5WZRBQB3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Haotian Gao, Jinliang Deng, Renhe Jiang, Xuan Song, Yuxin Ma, Zheng Dong","submitted_at":"2023-12-01T11:43:49Z","abstract_excerpt":"Spatiotemporal forecasting techniques are significant for various domains such as transportation, energy, and weather. Accurate prediction of spatiotemporal series remains challenging due to the complex spatiotemporal heterogeneity. In particular, current end-to-end models are limited by input length and thus often fall into spatiotemporal mirage, i.e., similar input time series followed by dissimilar future values and vice versa. To address these problems, we propose a novel self-supervised pre-training framework Spatial-Temporal-Decoupled Masked Pre-training (STD-MAE) that employs two decoup"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.00516","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/2312.00516/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":"2026-07-05T09:12:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zdu5Klot+oYU42ed+Xo8Cvh8GhTFa7W+bmX4mAk39wMxtNcZCPRiasxRPt3y5yZuTpHOUvCQrzqa+sG++dVMDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T01:06:39.656918Z"},"content_sha256":"4455ebdf3fc56bb34e1bdb03cd11d649823912b852b57308f59968869703e022","schema_version":"1.0","event_id":"sha256:4455ebdf3fc56bb34e1bdb03cd11d649823912b852b57308f59968869703e022"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J42VVDUU2ATXB6KFMA5WZRBQB3/bundle.json","state_url":"https://pith.science/pith/J42VVDUU2ATXB6KFMA5WZRBQB3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J42VVDUU2ATXB6KFMA5WZRBQB3/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":"2026-08-04T01:06:39Z","links":{"resolver":"https://pith.science/pith/J42VVDUU2ATXB6KFMA5WZRBQB3","bundle":"https://pith.science/pith/J42VVDUU2ATXB6KFMA5WZRBQB3/bundle.json","state":"https://pith.science/pith/J42VVDUU2ATXB6KFMA5WZRBQB3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J42VVDUU2ATXB6KFMA5WZRBQB3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:J42VVDUU2ATXB6KFMA5WZRBQB3","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":"173b28600773e056a9e7310848a09f12fe16c9f17c1a0cfd0de0100e3a4a4afa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-01T11:43:49Z","title_canon_sha256":"5f07ddcc1c8d5642f5b7adc652d746487e4cca103afeb0f1fda0b75aab6c0d62"},"schema_version":"1.0","source":{"id":"2312.00516","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.00516","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"arxiv_version","alias_value":"2312.00516v3","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.00516","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"pith_short_12","alias_value":"J42VVDUU2ATX","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"pith_short_16","alias_value":"J42VVDUU2ATXB6KF","created_at":"2026-07-05T09:12:57Z"},{"alias_kind":"pith_short_8","alias_value":"J42VVDUU","created_at":"2026-07-05T09:12:57Z"}],"graph_snapshots":[{"event_id":"sha256:4455ebdf3fc56bb34e1bdb03cd11d649823912b852b57308f59968869703e022","target":"graph","created_at":"2026-07-05T09:12:57Z","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/2312.00516/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spatiotemporal forecasting techniques are significant for various domains such as transportation, energy, and weather. Accurate prediction of spatiotemporal series remains challenging due to the complex spatiotemporal heterogeneity. In particular, current end-to-end models are limited by input length and thus often fall into spatiotemporal mirage, i.e., similar input time series followed by dissimilar future values and vice versa. To address these problems, we propose a novel self-supervised pre-training framework Spatial-Temporal-Decoupled Masked Pre-training (STD-MAE) that employs two decoup","authors_text":"Haotian Gao, Jinliang Deng, Renhe Jiang, Xuan Song, Yuxin Ma, Zheng Dong","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-01T11:43:49Z","title":"Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.00516","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":"sha256:31ab1b37f3652aa4bf04afc669fa40a0dc1da1ecf06c6f0f2c0837265c83d9bd","target":"record","created_at":"2026-07-05T09:12:57Z","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":"173b28600773e056a9e7310848a09f12fe16c9f17c1a0cfd0de0100e3a4a4afa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-01T11:43:49Z","title_canon_sha256":"5f07ddcc1c8d5642f5b7adc652d746487e4cca103afeb0f1fda0b75aab6c0d62"},"schema_version":"1.0","source":{"id":"2312.00516","kind":"arxiv","version":3}},"canonical_sha256":"4f355a8e94d02770f945603b6cc4300ee12d3c4052701a605984916f98641568","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4f355a8e94d02770f945603b6cc4300ee12d3c4052701a605984916f98641568","first_computed_at":"2026-07-05T09:12:57.291037Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:12:57.291037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rK5M4zFZiO2txUcnbj8zWUbtr8DkLbSyrbsLXJa2CMNsKeaxACKlwxBiRT51PYF0cwNvmkRIwtS9tF43gWsrAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:12:57.291595Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.00516","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:31ab1b37f3652aa4bf04afc669fa40a0dc1da1ecf06c6f0f2c0837265c83d9bd","sha256:4455ebdf3fc56bb34e1bdb03cd11d649823912b852b57308f59968869703e022"],"state_sha256":"117442d193d4ae6332539ba1d967920b234a917bf722e7f956241b7fdba1d442"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zw6qeQw8Y8pyPM/6DlB1ZMOzhIznJZWRj9bx9mgZFxHBtYd94LsXM9GdF0U94OwPFbBi8tO4kaxejA/aRo3aAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T01:06:39.661279Z","bundle_sha256":"f50471004fe012d4cdcaa550449adeff6297b19dde9f9d8e8dbfab4dca8ea3fa"}}