{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:JWKBYZV3UMGZXH3KTS5VU3ZX5Y","short_pith_number":"pith:JWKBYZV3","canonical_record":{"source":{"id":"2508.08919","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T13:15:51Z","cross_cats_sorted":[],"title_canon_sha256":"ebe105ba1180ad987470670453be08493356c9f0da1813590b1b008e5837daa0","abstract_canon_sha256":"f0aa3a67cd3952d883a51e4796384c834a66386f5182b383e63ce5bf943cf79b"},"schema_version":"1.0"},"canonical_sha256":"4d941c66bba30d9b9f6a9cbb5a6f37ee128f221082581c108b24723a7749e7fe","source":{"kind":"arxiv","id":"2508.08919","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.08919","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"arxiv_version","alias_value":"2508.08919v1","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.08919","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"pith_short_12","alias_value":"JWKBYZV3UMGZ","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"pith_short_16","alias_value":"JWKBYZV3UMGZXH3K","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"pith_short_8","alias_value":"JWKBYZV3","created_at":"2026-07-05T11:52:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:JWKBYZV3UMGZXH3KTS5VU3ZX5Y","target":"record","payload":{"canonical_record":{"source":{"id":"2508.08919","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T13:15:51Z","cross_cats_sorted":[],"title_canon_sha256":"ebe105ba1180ad987470670453be08493356c9f0da1813590b1b008e5837daa0","abstract_canon_sha256":"f0aa3a67cd3952d883a51e4796384c834a66386f5182b383e63ce5bf943cf79b"},"schema_version":"1.0"},"canonical_sha256":"4d941c66bba30d9b9f6a9cbb5a6f37ee128f221082581c108b24723a7749e7fe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:52:36.558014Z","signature_b64":"lmWTGO3bx7LfXMFl5mdgkDVbvAl+um3i9QNYI621bmmGhV8bVeZ9ZMc1g7DS1VIZ2Hzl2KX0NmKQvfGlSe/BAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d941c66bba30d9b9f6a9cbb5a6f37ee128f221082581c108b24723a7749e7fe","last_reissued_at":"2026-07-05T11:52:36.557446Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:52:36.557446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.08919","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:52:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Or1ysVpsj1BZmEEwUfismY+Cdyi60wvwqOOYl2iAf363P27I63gGYhXSbOUbqXzuuV9Eyac5pj9WjDEVGQDmBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T03:55:58.344128Z"},"content_sha256":"263d831c4a5fd62cd177ed9542deca261d3b887586dd737b0c7e59e22661415b","schema_version":"1.0","event_id":"sha256:263d831c4a5fd62cd177ed9542deca261d3b887586dd737b0c7e59e22661415b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:JWKBYZV3UMGZXH3KTS5VU3ZX5Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Stationarity Exploration for Multivariate Time Series Forecasting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chun Yang, Hao Liu, Rui Ma, Xiaobin Zhu, Zhang xiaoxing","submitted_at":"2025-08-12T13:15:51Z","abstract_excerpt":"Deep learning-based time series forecasting has found widespread applications. Recently, converting time series data into the frequency domain for forecasting has become popular for accurately exploring periodic patterns. However, existing methods often cannot effectively explore stationary information from complex intertwined frequency components. In this paper, we propose a simple yet effective Amplitude-Phase Reconstruct Network (APRNet) that models the inter-relationships of amplitude and phase, which prevents the amplitude and phase from being constrained by different physical quantities,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.08919","kind":"arxiv","version":1},"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/2508.08919/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":"2026-07-05T11:52:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8n3Ur5QJfWj6MAzBO1RnOQ3E14v2tLThievp9uw2wopC/o/Bnpze/AUFa+Z8MGYw1tL3WJlhOxBvOAaaMR7VCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T03:55:58.344747Z"},"content_sha256":"6d32067ce0e305faf16622e241e590089602f75c3b408013c94a08a878fd481f","schema_version":"1.0","event_id":"sha256:6d32067ce0e305faf16622e241e590089602f75c3b408013c94a08a878fd481f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JWKBYZV3UMGZXH3KTS5VU3ZX5Y/bundle.json","state_url":"https://pith.science/pith/JWKBYZV3UMGZXH3KTS5VU3ZX5Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JWKBYZV3UMGZXH3KTS5VU3ZX5Y/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":"2026-08-23T03:55:58Z","links":{"resolver":"https://pith.science/pith/JWKBYZV3UMGZXH3KTS5VU3ZX5Y","bundle":"https://pith.science/pith/JWKBYZV3UMGZXH3KTS5VU3ZX5Y/bundle.json","state":"https://pith.science/pith/JWKBYZV3UMGZXH3KTS5VU3ZX5Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JWKBYZV3UMGZXH3KTS5VU3ZX5Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:JWKBYZV3UMGZXH3KTS5VU3ZX5Y","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":"f0aa3a67cd3952d883a51e4796384c834a66386f5182b383e63ce5bf943cf79b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T13:15:51Z","title_canon_sha256":"ebe105ba1180ad987470670453be08493356c9f0da1813590b1b008e5837daa0"},"schema_version":"1.0","source":{"id":"2508.08919","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.08919","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"arxiv_version","alias_value":"2508.08919v1","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.08919","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"pith_short_12","alias_value":"JWKBYZV3UMGZ","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"pith_short_16","alias_value":"JWKBYZV3UMGZXH3K","created_at":"2026-07-05T11:52:36Z"},{"alias_kind":"pith_short_8","alias_value":"JWKBYZV3","created_at":"2026-07-05T11:52:36Z"}],"graph_snapshots":[{"event_id":"sha256:6d32067ce0e305faf16622e241e590089602f75c3b408013c94a08a878fd481f","target":"graph","created_at":"2026-07-05T11:52:36Z","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/2508.08919/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning-based time series forecasting has found widespread applications. Recently, converting time series data into the frequency domain for forecasting has become popular for accurately exploring periodic patterns. However, existing methods often cannot effectively explore stationary information from complex intertwined frequency components. In this paper, we propose a simple yet effective Amplitude-Phase Reconstruct Network (APRNet) that models the inter-relationships of amplitude and phase, which prevents the amplitude and phase from being constrained by different physical quantities,","authors_text":"Chun Yang, Hao Liu, Rui Ma, Xiaobin Zhu, Zhang xiaoxing","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T13:15:51Z","title":"Stationarity Exploration for Multivariate Time Series Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.08919","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":"sha256:263d831c4a5fd62cd177ed9542deca261d3b887586dd737b0c7e59e22661415b","target":"record","created_at":"2026-07-05T11:52:36Z","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":"f0aa3a67cd3952d883a51e4796384c834a66386f5182b383e63ce5bf943cf79b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T13:15:51Z","title_canon_sha256":"ebe105ba1180ad987470670453be08493356c9f0da1813590b1b008e5837daa0"},"schema_version":"1.0","source":{"id":"2508.08919","kind":"arxiv","version":1}},"canonical_sha256":"4d941c66bba30d9b9f6a9cbb5a6f37ee128f221082581c108b24723a7749e7fe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4d941c66bba30d9b9f6a9cbb5a6f37ee128f221082581c108b24723a7749e7fe","first_computed_at":"2026-07-05T11:52:36.557446Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:52:36.557446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lmWTGO3bx7LfXMFl5mdgkDVbvAl+um3i9QNYI621bmmGhV8bVeZ9ZMc1g7DS1VIZ2Hzl2KX0NmKQvfGlSe/BAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:52:36.558014Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.08919","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:263d831c4a5fd62cd177ed9542deca261d3b887586dd737b0c7e59e22661415b","sha256:6d32067ce0e305faf16622e241e590089602f75c3b408013c94a08a878fd481f"],"state_sha256":"7cb36c98ca50bb065efd7ecabdfb485f657f25c360129dae32d3935e54e97a84"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T0gpLwzqCpSrGofzh08eBv9EPH+4LPQDin0fFTA6n51BxkDCy87VCuGCEULJHDC/ad008wabAgPw2F/RYfdSAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T03:55:58.349714Z","bundle_sha256":"47283ef2d56d6a5af43b7ba2788c485e4a481967487d5062a9319389b5d2a56c"}}