{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QDIRDCH3P55NS4EHQXXVZCRFST","short_pith_number":"pith:QDIRDCH3","canonical_record":{"source":{"id":"2402.12767","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T07:16:12Z","cross_cats_sorted":[],"title_canon_sha256":"8449d021e518269a05b68e54c00aeba2662d9e494a3356da2d51c2f4f9bae550","abstract_canon_sha256":"ee5c9dc4f0a765e097d33b6e353ebdefcbd6047d03c90eeff76b0c472d50d9b5"},"schema_version":"1.0"},"canonical_sha256":"80d11188fb7f7ad9708785ef5c8a2594feff76fc2f4515d6e48e40ad7da29ab9","source":{"kind":"arxiv","id":"2402.12767","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.12767","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"arxiv_version","alias_value":"2402.12767v4","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.12767","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"pith_short_12","alias_value":"QDIRDCH3P55N","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"pith_short_16","alias_value":"QDIRDCH3P55NS4EH","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"pith_short_8","alias_value":"QDIRDCH3","created_at":"2026-07-05T10:27:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QDIRDCH3P55NS4EHQXXVZCRFST","target":"record","payload":{"canonical_record":{"source":{"id":"2402.12767","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T07:16:12Z","cross_cats_sorted":[],"title_canon_sha256":"8449d021e518269a05b68e54c00aeba2662d9e494a3356da2d51c2f4f9bae550","abstract_canon_sha256":"ee5c9dc4f0a765e097d33b6e353ebdefcbd6047d03c90eeff76b0c472d50d9b5"},"schema_version":"1.0"},"canonical_sha256":"80d11188fb7f7ad9708785ef5c8a2594feff76fc2f4515d6e48e40ad7da29ab9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:27:07.804884Z","signature_b64":"82cyZxjxtLswv7kZSVRMnJK7etL0ejgHUULsKYIh+Feyhd3XlXxYSiOam4/f68l8/fLdS462N6eeQcyRzjLcAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"80d11188fb7f7ad9708785ef5c8a2594feff76fc2f4515d6e48e40ad7da29ab9","last_reissued_at":"2026-07-05T10:27:07.804249Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:27:07.804249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.12767","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:27:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GeSDm/n/Z7FyMPsr+31QbDYO0mHWtuwZvHi1/nxlVPkOKRWIRTLFhNUhFrv1kLgj9/6XHe84sLPbkfSDk3KNCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T12:24:24.578054Z"},"content_sha256":"e101f50ac5ec4078177cdc6330f4d0f60aa98899f9413a6029bbbd529051e0dc","schema_version":"1.0","event_id":"sha256:e101f50ac5ec4078177cdc6330f4d0f60aa98899f9413a6029bbbd529051e0dc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QDIRDCH3P55NS4EHQXXVZCRFST","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Nonstationary Time Series Forecasting via Unknown Distribution Adaptation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Guangyi Chen, Haiqin Huang, Kun Zhang, Ruichu Cai, Xiangchen Song, Yifan Shen, Zhengming Chen, Zhenhui Yang, Zijian Li","submitted_at":"2024-02-20T07:16:12Z","abstract_excerpt":"As environments evolve, temporal distribution shifts can degrade time series forecasting performance. A straightforward solution is to adapt to nonstationary changes while preserving stationary dependencies. Hence, some methods disentangle stationary and nonstationary components by assuming uniform distribution shifts, but it is impractical since when the distribution changes is unknown. To address this challenge, we propose the \\textbf{U}nknown \\textbf{D}istribution \\textbf{A}daptation (\\textbf{UDA}) model for nonstationary time series forecasting, which detects when distribution shifts occur"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.12767","kind":"arxiv","version":4},"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/2402.12767/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":"2026-07-05T10:27:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EIOYCX0j7EfGvgFDGiMfuyMvLPLUYDaq1mEeVNiVA2a98wvC5cAsU8FI7rbmDduYM5hQ+QS/L8zxYvQa/XswCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T12:24:24.578452Z"},"content_sha256":"6c947f72f276928a0db7c534c3d605e0a202a793be38dce373317521af0cf233","schema_version":"1.0","event_id":"sha256:6c947f72f276928a0db7c534c3d605e0a202a793be38dce373317521af0cf233"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QDIRDCH3P55NS4EHQXXVZCRFST/bundle.json","state_url":"https://pith.science/pith/QDIRDCH3P55NS4EHQXXVZCRFST/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QDIRDCH3P55NS4EHQXXVZCRFST/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":"2026-07-14T12:24:24Z","links":{"resolver":"https://pith.science/pith/QDIRDCH3P55NS4EHQXXVZCRFST","bundle":"https://pith.science/pith/QDIRDCH3P55NS4EHQXXVZCRFST/bundle.json","state":"https://pith.science/pith/QDIRDCH3P55NS4EHQXXVZCRFST/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QDIRDCH3P55NS4EHQXXVZCRFST/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QDIRDCH3P55NS4EHQXXVZCRFST","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":"ee5c9dc4f0a765e097d33b6e353ebdefcbd6047d03c90eeff76b0c472d50d9b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T07:16:12Z","title_canon_sha256":"8449d021e518269a05b68e54c00aeba2662d9e494a3356da2d51c2f4f9bae550"},"schema_version":"1.0","source":{"id":"2402.12767","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.12767","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"arxiv_version","alias_value":"2402.12767v4","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.12767","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"pith_short_12","alias_value":"QDIRDCH3P55N","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"pith_short_16","alias_value":"QDIRDCH3P55NS4EH","created_at":"2026-07-05T10:27:07Z"},{"alias_kind":"pith_short_8","alias_value":"QDIRDCH3","created_at":"2026-07-05T10:27:07Z"}],"graph_snapshots":[{"event_id":"sha256:6c947f72f276928a0db7c534c3d605e0a202a793be38dce373317521af0cf233","target":"graph","created_at":"2026-07-05T10:27:07Z","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/2402.12767/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As environments evolve, temporal distribution shifts can degrade time series forecasting performance. A straightforward solution is to adapt to nonstationary changes while preserving stationary dependencies. Hence, some methods disentangle stationary and nonstationary components by assuming uniform distribution shifts, but it is impractical since when the distribution changes is unknown. To address this challenge, we propose the \\textbf{U}nknown \\textbf{D}istribution \\textbf{A}daptation (\\textbf{UDA}) model for nonstationary time series forecasting, which detects when distribution shifts occur","authors_text":"Guangyi Chen, Haiqin Huang, Kun Zhang, Ruichu Cai, Xiangchen Song, Yifan Shen, Zhengming Chen, Zhenhui Yang, Zijian Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T07:16:12Z","title":"Nonstationary Time Series Forecasting via Unknown Distribution Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.12767","kind":"arxiv","version":4},"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:e101f50ac5ec4078177cdc6330f4d0f60aa98899f9413a6029bbbd529051e0dc","target":"record","created_at":"2026-07-05T10:27:07Z","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":"ee5c9dc4f0a765e097d33b6e353ebdefcbd6047d03c90eeff76b0c472d50d9b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T07:16:12Z","title_canon_sha256":"8449d021e518269a05b68e54c00aeba2662d9e494a3356da2d51c2f4f9bae550"},"schema_version":"1.0","source":{"id":"2402.12767","kind":"arxiv","version":4}},"canonical_sha256":"80d11188fb7f7ad9708785ef5c8a2594feff76fc2f4515d6e48e40ad7da29ab9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"80d11188fb7f7ad9708785ef5c8a2594feff76fc2f4515d6e48e40ad7da29ab9","first_computed_at":"2026-07-05T10:27:07.804249Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:27:07.804249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"82cyZxjxtLswv7kZSVRMnJK7etL0ejgHUULsKYIh+Feyhd3XlXxYSiOam4/f68l8/fLdS462N6eeQcyRzjLcAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:27:07.804884Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.12767","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e101f50ac5ec4078177cdc6330f4d0f60aa98899f9413a6029bbbd529051e0dc","sha256:6c947f72f276928a0db7c534c3d605e0a202a793be38dce373317521af0cf233"],"state_sha256":"f78fb90506c585f469fcb6d8578ba584405b33b267ca3d62067c2dcd4d9698f2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hYC4DJckCG8mVIY3HLUoDnsCnNwRvn5sHJxmVEAhEy1aRrUnOxD6Abr+4YLr3htbwfcYhaFBWerTyTDd/rsoDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-14T12:24:24.581014Z","bundle_sha256":"a3c4708821c424c376ed7fd1682519d3b4cf27ea782a50c48cee80a08a906233"}}