{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:R2HM75JQLR3UWJUZU7NVGXMHOD","short_pith_number":"pith:R2HM75JQ","canonical_record":{"source":{"id":"2402.19072","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T11:54:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bb4bca8a5b329e068d29bca6254a9d93bd489e29df65dd15a217e705ed5c2270","abstract_canon_sha256":"5026b3bd3a5369b1b009e212810d19992c3a8256ef9677982243a32ffa1209f5"},"schema_version":"1.0"},"canonical_sha256":"8e8ecff5305c774b2699a7db535d8770ddcf1fe28f071c66f949dc8adab9e950","source":{"kind":"arxiv","id":"2402.19072","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.19072","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"arxiv_version","alias_value":"2402.19072v4","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.19072","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"pith_short_12","alias_value":"R2HM75JQLR3U","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"pith_short_16","alias_value":"R2HM75JQLR3UWJUZ","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"pith_short_8","alias_value":"R2HM75JQ","created_at":"2026-07-05T09:33:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:R2HM75JQLR3UWJUZU7NVGXMHOD","target":"record","payload":{"canonical_record":{"source":{"id":"2402.19072","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T11:54:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bb4bca8a5b329e068d29bca6254a9d93bd489e29df65dd15a217e705ed5c2270","abstract_canon_sha256":"5026b3bd3a5369b1b009e212810d19992c3a8256ef9677982243a32ffa1209f5"},"schema_version":"1.0"},"canonical_sha256":"8e8ecff5305c774b2699a7db535d8770ddcf1fe28f071c66f949dc8adab9e950","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:33:29.269903Z","signature_b64":"U4g3dCWSBZqkxHrWRhBrKZje+29qpNxg650LyeIEf3rJCptlewkIgM2SgTgzatMpVZOePaVBBfCN8C1MDip5AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e8ecff5305c774b2699a7db535d8770ddcf1fe28f071c66f949dc8adab9e950","last_reissued_at":"2026-07-05T09:33:29.269376Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:33:29.269376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.19072","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":"2026-07-05T09:33:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ur1rcYEJoMO46IENtbp42BZMP7rGWRFeDXVOQO0198QaRDcOD9kHnMpiI2T3tqmWKWxxyZ8srggroA8o5CsSDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:50:15.742853Z"},"content_sha256":"be8eb9d3821930e3ad4faf20d436e2f6cd1cf8cf71b8b1b7b2a2ca48bfc0d05d","schema_version":"1.0","event_id":"sha256:be8eb9d3821930e3ad4faf20d436e2f6cd1cf8cf71b8b1b7b2a2ca48bfc0d05d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:R2HM75JQLR3UWJUZU7NVGXMHOD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Guo Qin, Haixu Wu, Haoran Zhang, Jianmin Wang, Jiaxiang Dong, Mingsheng Long, Yong Liu, Yunzhong Qiu, Yuxuan Wang","submitted_at":"2024-02-29T11:54:35Z","abstract_excerpt":"Deep models have demonstrated remarkable performance in time series forecasting. However, due to the partially-observed nature of real-world applications, solely focusing on the target of interest, so-called endogenous variables, is usually insufficient to guarantee accurate forecasting. Notably, a system is often recorded into multiple variables, where the exogenous variables can provide valuable external information for endogenous variables. Thus, unlike well-established multivariate or univariate forecasting paradigms that either treat all the variables equally or ignore exogenous informati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.19072","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/2402.19072/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":"2026-07-05T09:33:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+xmlLW+IDca9h51+gFO4rHeUN85OFceVDYZvcI2aE/HEkWA45WKI0DSQYwhiychbYH1eHeFjWwMc3gZmFTeeAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:50:15.744146Z"},"content_sha256":"2165aa81a9fd1842b9412d38a03726826dfaaa1dc74c042099096df328d5a681","schema_version":"1.0","event_id":"sha256:2165aa81a9fd1842b9412d38a03726826dfaaa1dc74c042099096df328d5a681"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R2HM75JQLR3UWJUZU7NVGXMHOD/bundle.json","state_url":"https://pith.science/pith/R2HM75JQLR3UWJUZU7NVGXMHOD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R2HM75JQLR3UWJUZU7NVGXMHOD/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":"2026-08-06T04:50:15Z","links":{"resolver":"https://pith.science/pith/R2HM75JQLR3UWJUZU7NVGXMHOD","bundle":"https://pith.science/pith/R2HM75JQLR3UWJUZU7NVGXMHOD/bundle.json","state":"https://pith.science/pith/R2HM75JQLR3UWJUZU7NVGXMHOD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R2HM75JQLR3UWJUZU7NVGXMHOD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:R2HM75JQLR3UWJUZU7NVGXMHOD","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":"5026b3bd3a5369b1b009e212810d19992c3a8256ef9677982243a32ffa1209f5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T11:54:35Z","title_canon_sha256":"bb4bca8a5b329e068d29bca6254a9d93bd489e29df65dd15a217e705ed5c2270"},"schema_version":"1.0","source":{"id":"2402.19072","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.19072","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"arxiv_version","alias_value":"2402.19072v4","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.19072","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"pith_short_12","alias_value":"R2HM75JQLR3U","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"pith_short_16","alias_value":"R2HM75JQLR3UWJUZ","created_at":"2026-07-05T09:33:29Z"},{"alias_kind":"pith_short_8","alias_value":"R2HM75JQ","created_at":"2026-07-05T09:33:29Z"}],"graph_snapshots":[{"event_id":"sha256:2165aa81a9fd1842b9412d38a03726826dfaaa1dc74c042099096df328d5a681","target":"graph","created_at":"2026-07-05T09:33:29Z","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/2402.19072/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep models have demonstrated remarkable performance in time series forecasting. However, due to the partially-observed nature of real-world applications, solely focusing on the target of interest, so-called endogenous variables, is usually insufficient to guarantee accurate forecasting. Notably, a system is often recorded into multiple variables, where the exogenous variables can provide valuable external information for endogenous variables. Thus, unlike well-established multivariate or univariate forecasting paradigms that either treat all the variables equally or ignore exogenous informati","authors_text":"Guo Qin, Haixu Wu, Haoran Zhang, Jianmin Wang, Jiaxiang Dong, Mingsheng Long, Yong Liu, Yunzhong Qiu, Yuxuan Wang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T11:54:35Z","title":"TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.19072","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:be8eb9d3821930e3ad4faf20d436e2f6cd1cf8cf71b8b1b7b2a2ca48bfc0d05d","target":"record","created_at":"2026-07-05T09:33:29Z","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":"5026b3bd3a5369b1b009e212810d19992c3a8256ef9677982243a32ffa1209f5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T11:54:35Z","title_canon_sha256":"bb4bca8a5b329e068d29bca6254a9d93bd489e29df65dd15a217e705ed5c2270"},"schema_version":"1.0","source":{"id":"2402.19072","kind":"arxiv","version":4}},"canonical_sha256":"8e8ecff5305c774b2699a7db535d8770ddcf1fe28f071c66f949dc8adab9e950","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e8ecff5305c774b2699a7db535d8770ddcf1fe28f071c66f949dc8adab9e950","first_computed_at":"2026-07-05T09:33:29.269376Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:33:29.269376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"U4g3dCWSBZqkxHrWRhBrKZje+29qpNxg650LyeIEf3rJCptlewkIgM2SgTgzatMpVZOePaVBBfCN8C1MDip5AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:33:29.269903Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.19072","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be8eb9d3821930e3ad4faf20d436e2f6cd1cf8cf71b8b1b7b2a2ca48bfc0d05d","sha256:2165aa81a9fd1842b9412d38a03726826dfaaa1dc74c042099096df328d5a681"],"state_sha256":"43406e1832c16d88aa9a2b1bfb715a53fb78c9c265fdd0230db196ac352c4057"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7TEswkIv3fLTdidMdI5ignoqrjn6BZs5ew9fPkgP2+BR0CuUVUS9OFRHImu66cL0KOSRZcT1LQbNiNBQ22eqDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T04:50:15.751487Z","bundle_sha256":"9f1fea366751a59a2d57b64eb09206183d1b10506d340b9e33a2c49f105d8e20"}}