{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TT5DPV22W5E5SXB3WX3SX2H5EO","short_pith_number":"pith:TT5DPV22","canonical_record":{"source":{"id":"2410.04803","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T07:27:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"8c14942ab233785ded8a33fee4777d644f5e5c800b92749a082c536cb009d75c","abstract_canon_sha256":"1cc1cbb975c685d2a8269309666ec9fb965f55efbf1f2fbdd19dc2d934783d51"},"schema_version":"1.0"},"canonical_sha256":"9cfa37d75ab749d95c3bb5f72be8fd238a97f08e1c35c55d00773ab4c1bdc8e7","source":{"kind":"arxiv","id":"2410.04803","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04803","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04803v4","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04803","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_12","alias_value":"TT5DPV22W5E5","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_16","alias_value":"TT5DPV22W5E5SXB3","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_8","alias_value":"TT5DPV22","created_at":"2026-07-05T10:22:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TT5DPV22W5E5SXB3WX3SX2H5EO","target":"record","payload":{"canonical_record":{"source":{"id":"2410.04803","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T07:27:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"8c14942ab233785ded8a33fee4777d644f5e5c800b92749a082c536cb009d75c","abstract_canon_sha256":"1cc1cbb975c685d2a8269309666ec9fb965f55efbf1f2fbdd19dc2d934783d51"},"schema_version":"1.0"},"canonical_sha256":"9cfa37d75ab749d95c3bb5f72be8fd238a97f08e1c35c55d00773ab4c1bdc8e7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:22:06.433852Z","signature_b64":"UHJkGOIXfTuQyTeZGUZRTSzonrD6Dkwo/WNZSCPu8lGl7JYx+R5XbLBjAx+oX8r5zXf1B7nu3xfXMHngVNszCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9cfa37d75ab749d95c3bb5f72be8fd238a97f08e1c35c55d00773ab4c1bdc8e7","last_reissued_at":"2026-07-05T10:22:06.433321Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:22:06.433321Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.04803","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":"2026-07-05T10:22:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/jh4B7FaBSaBYZq9m17MrV5lvR30IMieAuHx7HrtS6vGMSm8Uu7PL3SDtr63T9oOvPEit+6OTy/7NZAT3M3ACg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:05:51.259521Z"},"content_sha256":"e9ffb9ddb018b490c643a7c28ca1c0afde595090f063b91e6dda8dce44755c08","schema_version":"1.0","event_id":"sha256:e9ffb9ddb018b490c643a7c28ca1c0afde595090f063b91e6dda8dce44755c08"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TT5DPV22W5E5SXB3WX3SX2H5EO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Guo Qin, Jianmin Wang, Mingsheng Long, Xiangdong Huang, Yong Liu","submitted_at":"2024-10-07T07:27:39Z","abstract_excerpt":"We present Timer-XL, a causal Transformer for unified time series forecasting. To uniformly predict multidimensional time series, we generalize next token prediction, predominantly adopted for 1D token sequences, to multivariate next token prediction. The paradigm formulates various forecasting tasks as a long-context prediction problem. We opt for decoder-only Transformers that capture causal dependencies from varying-length contexts for unified forecasting, making predictions on non-stationary univariate time series, multivariate series with complicated dynamics and correlations, as well as "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04803","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/2410.04803/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":"2026-07-05T10:22:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hDZFJGMSo2wDgiBaHdWCt36Uus34cQQHZBDpkshMhchCYjwkaORP18SXL8nuuCw8lL0h5gR3YMHslGvDuO+1Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:05:51.260473Z"},"content_sha256":"90fd69396b7109771e0c2368c1adf5b9a3a0213353b20603a909c149ced7868a","schema_version":"1.0","event_id":"sha256:90fd69396b7109771e0c2368c1adf5b9a3a0213353b20603a909c149ced7868a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TT5DPV22W5E5SXB3WX3SX2H5EO/bundle.json","state_url":"https://pith.science/pith/TT5DPV22W5E5SXB3WX3SX2H5EO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TT5DPV22W5E5SXB3WX3SX2H5EO/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":"2026-08-04T21:05:51Z","links":{"resolver":"https://pith.science/pith/TT5DPV22W5E5SXB3WX3SX2H5EO","bundle":"https://pith.science/pith/TT5DPV22W5E5SXB3WX3SX2H5EO/bundle.json","state":"https://pith.science/pith/TT5DPV22W5E5SXB3WX3SX2H5EO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TT5DPV22W5E5SXB3WX3SX2H5EO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TT5DPV22W5E5SXB3WX3SX2H5EO","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":"1cc1cbb975c685d2a8269309666ec9fb965f55efbf1f2fbdd19dc2d934783d51","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T07:27:39Z","title_canon_sha256":"8c14942ab233785ded8a33fee4777d644f5e5c800b92749a082c536cb009d75c"},"schema_version":"1.0","source":{"id":"2410.04803","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04803","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04803v4","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04803","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_12","alias_value":"TT5DPV22W5E5","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_16","alias_value":"TT5DPV22W5E5SXB3","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_8","alias_value":"TT5DPV22","created_at":"2026-07-05T10:22:06Z"}],"graph_snapshots":[{"event_id":"sha256:90fd69396b7109771e0c2368c1adf5b9a3a0213353b20603a909c149ced7868a","target":"graph","created_at":"2026-07-05T10:22:06Z","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/2410.04803/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present Timer-XL, a causal Transformer for unified time series forecasting. To uniformly predict multidimensional time series, we generalize next token prediction, predominantly adopted for 1D token sequences, to multivariate next token prediction. The paradigm formulates various forecasting tasks as a long-context prediction problem. We opt for decoder-only Transformers that capture causal dependencies from varying-length contexts for unified forecasting, making predictions on non-stationary univariate time series, multivariate series with complicated dynamics and correlations, as well as ","authors_text":"Guo Qin, Jianmin Wang, Mingsheng Long, Xiangdong Huang, Yong Liu","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04803","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:e9ffb9ddb018b490c643a7c28ca1c0afde595090f063b91e6dda8dce44755c08","target":"record","created_at":"2026-07-05T10:22:06Z","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":"1cc1cbb975c685d2a8269309666ec9fb965f55efbf1f2fbdd19dc2d934783d51","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T07:27:39Z","title_canon_sha256":"8c14942ab233785ded8a33fee4777d644f5e5c800b92749a082c536cb009d75c"},"schema_version":"1.0","source":{"id":"2410.04803","kind":"arxiv","version":4}},"canonical_sha256":"9cfa37d75ab749d95c3bb5f72be8fd238a97f08e1c35c55d00773ab4c1bdc8e7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9cfa37d75ab749d95c3bb5f72be8fd238a97f08e1c35c55d00773ab4c1bdc8e7","first_computed_at":"2026-07-05T10:22:06.433321Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:22:06.433321Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UHJkGOIXfTuQyTeZGUZRTSzonrD6Dkwo/WNZSCPu8lGl7JYx+R5XbLBjAx+oX8r5zXf1B7nu3xfXMHngVNszCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:22:06.433852Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.04803","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e9ffb9ddb018b490c643a7c28ca1c0afde595090f063b91e6dda8dce44755c08","sha256:90fd69396b7109771e0c2368c1adf5b9a3a0213353b20603a909c149ced7868a"],"state_sha256":"528dda7f5f7b45690a46a97599e8147fee58ff88882dce5b222fae7a635fc58b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GNSjuHD/519B9vy/zWpCPg3t5Va75rpfFzsAOAi750C++7pCljQKy2uVux2bNrm2ZTNFdo/TY0JkredJ+nMxDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T21:05:51.284449Z","bundle_sha256":"3cedccf253eb33faf59164faf6f0e9d4e6adae864113eabedc54ed096125903a"}}