{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:6YROJ46IMHWPXSU6ZXBZ4HCALP","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":"ac75dc0c69f555eea115123bac212509bbbc103b3aab9743551bb579edd18434","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-13T07:30:12Z","title_canon_sha256":"fef254a55935de04183b99ee00e57499c81acee306060204d503957dd7e1a7a5"},"schema_version":"1.0","source":{"id":"2506.11528","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.11528","created_at":"2026-07-05T11:21:06Z"},{"alias_kind":"arxiv_version","alias_value":"2506.11528v1","created_at":"2026-07-05T11:21:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.11528","created_at":"2026-07-05T11:21:06Z"},{"alias_kind":"pith_short_12","alias_value":"6YROJ46IMHWP","created_at":"2026-07-05T11:21:06Z"},{"alias_kind":"pith_short_16","alias_value":"6YROJ46IMHWPXSU6","created_at":"2026-07-05T11:21:06Z"},{"alias_kind":"pith_short_8","alias_value":"6YROJ46I","created_at":"2026-07-05T11:21:06Z"}],"graph_snapshots":[{"event_id":"sha256:c24ebcc182ecfae1d22fb5148223b337513b55a45483baf0ffbcf6917dfe2d15","target":"graph","created_at":"2026-07-05T11:21:06Z","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/2506.11528/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Predicting time-series is of great importance in various scientific and engineering fields. However, in the context of limited and noisy data, accurately predicting dynamics of all variables in a high-dimensional system is a challenging task due to their nonlinearity and also complex interactions. Current methods including deep learning approaches often perform poorly for real-world systems under such circumstances. This study introduces the Delayformer framework for simultaneously predicting dynamics of all variables, by developing a novel multivariate spatiotemporal information (mvSTI) trans","authors_text":"Luonan Chen, Peng Tao, Zijian Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-13T07:30:12Z","title":"Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.11528","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":"sha256:114f2d6feb953f02ad0c73f40dfe768ccad9de733108c4b5f3550fc33be5cecb","target":"record","created_at":"2026-07-05T11:21:06Z","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":"ac75dc0c69f555eea115123bac212509bbbc103b3aab9743551bb579edd18434","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-13T07:30:12Z","title_canon_sha256":"fef254a55935de04183b99ee00e57499c81acee306060204d503957dd7e1a7a5"},"schema_version":"1.0","source":{"id":"2506.11528","kind":"arxiv","version":1}},"canonical_sha256":"f622e4f3c861ecfbca9ecdc39e1c405bccc749e8f7e9b5d5ac893e9fb611cdbf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f622e4f3c861ecfbca9ecdc39e1c405bccc749e8f7e9b5d5ac893e9fb611cdbf","first_computed_at":"2026-07-05T11:21:06.132999Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:21:06.132999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tGwSMjAx2USlS1j0EO7WqPO3EA3gwae6qxC0gKh1AvGapr8bMagLBgnRkGZ2PzgpIfLCwSyvehOz9kZ/ZKlxAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:21:06.133411Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.11528","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:114f2d6feb953f02ad0c73f40dfe768ccad9de733108c4b5f3550fc33be5cecb","sha256:c24ebcc182ecfae1d22fb5148223b337513b55a45483baf0ffbcf6917dfe2d15"],"state_sha256":"0ad2bbee021eb8bd5384561b162bde464bc5075a0a25941c1893765eb864d842"}