{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UXGCIJNMJE2M7GCPDESTGBYZJN","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":"8819715f1281287eb7cb5d72bf4eaa12386156a39d8a3594ddf23e13e558581c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-29T02:52:59Z","title_canon_sha256":"8c994cfbc2f5c93fae614b39b15995baff5d719c9b4ff50f271aa7eb430d28b8"},"schema_version":"1.0","source":{"id":"2505.23017","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.23017","created_at":"2026-07-05T11:43:32Z"},{"alias_kind":"arxiv_version","alias_value":"2505.23017v3","created_at":"2026-07-05T11:43:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.23017","created_at":"2026-07-05T11:43:32Z"},{"alias_kind":"pith_short_12","alias_value":"UXGCIJNMJE2M","created_at":"2026-07-05T11:43:32Z"},{"alias_kind":"pith_short_16","alias_value":"UXGCIJNMJE2M7GCP","created_at":"2026-07-05T11:43:32Z"},{"alias_kind":"pith_short_8","alias_value":"UXGCIJNM","created_at":"2026-07-05T11:43:32Z"}],"graph_snapshots":[{"event_id":"sha256:6d7c4b079b58d74b6fe70d7bf8498bae6ce178b3890ed7eeb10d78276ef3c4f5","target":"graph","created_at":"2026-07-05T11:43:32Z","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/2505.23017/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Probabilistic Time Series Forecasting (PTSF) plays a crucial role in decision-making across various fields, including economics, energy, and transportation. Most existing methods excell at short-term forecasting, while overlooking the hurdles of Long-term Probabilistic Time Series Forecasting (LPTSF). As the forecast horizon extends, the inherent nonlinear dynamics have a significant adverse effect on prediction accuracy, and make generative models inefficient by increasing the cost of each iteration. To overcome these limitations, we introduce $K^2$VAE, an efficient VAE-based generative model","authors_text":"Bin Yang, Chenjuan Guo, Hongfan Gao, Jilin Hu, Xiangfei Qiu, Xingjian Wu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-29T02:52:59Z","title":"$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.23017","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:c9f9cec76cdbdc831e54d04f680ef1336c03856fe63cd40652cda64366453491","target":"record","created_at":"2026-07-05T11:43:32Z","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":"8819715f1281287eb7cb5d72bf4eaa12386156a39d8a3594ddf23e13e558581c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-29T02:52:59Z","title_canon_sha256":"8c994cfbc2f5c93fae614b39b15995baff5d719c9b4ff50f271aa7eb430d28b8"},"schema_version":"1.0","source":{"id":"2505.23017","kind":"arxiv","version":3}},"canonical_sha256":"a5cc2425ac4934cf984f19253307194b7e71fdfca8034a75425b6ff83a3ebc7a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5cc2425ac4934cf984f19253307194b7e71fdfca8034a75425b6ff83a3ebc7a","first_computed_at":"2026-07-05T11:43:32.466493Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:43:32.466493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mnmUphkZURanADvnnUCvGT/5oH1BqGvihik8YL0dfwXVDnB7STi/eJ4jDjXAcmYFQESxLY+G8i1NN9jkSZ9jBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:43:32.467064Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.23017","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c9f9cec76cdbdc831e54d04f680ef1336c03856fe63cd40652cda64366453491","sha256:6d7c4b079b58d74b6fe70d7bf8498bae6ce178b3890ed7eeb10d78276ef3c4f5"],"state_sha256":"34ab74a529fa962e0ff50f1f4ed81f9c23f8f868a4bcb63eac2720d973b9fb6a"}