{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:CQL2YRHIXARBDIHRDR3BF5EKWC","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":"e96dd398a0369e04aac7100b4f5ed05b86a4ef36c622bc86edb73a47535461d6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-26T10:17:09Z","title_canon_sha256":"c70ef89aeb3d4874ea6b3aa95f66dd45553862cfa2f74a45bb932632cf130e8a"},"schema_version":"1.0","source":{"id":"2605.30376","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30376","created_at":"2026-06-01T00:02:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30376v1","created_at":"2026-06-01T00:02:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30376","created_at":"2026-06-01T00:02:08Z"},{"alias_kind":"pith_short_12","alias_value":"CQL2YRHIXARB","created_at":"2026-06-01T00:02:08Z"},{"alias_kind":"pith_short_16","alias_value":"CQL2YRHIXARBDIHR","created_at":"2026-06-01T00:02:08Z"},{"alias_kind":"pith_short_8","alias_value":"CQL2YRHI","created_at":"2026-06-01T00:02:08Z"}],"graph_snapshots":[{"event_id":"sha256:f380e80eede6a9a0e581bcc881330da9275d40f9502ed8739e505013ba278fb4","target":"graph","created_at":"2026-06-01T00:02:08Z","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/2605.30376/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Modern time series architectures face a fundamental trade-off: channel-independent models scale well with increasing data volume but ignore critical inter-channel dependencies, while channel-dependent models are expressive but remain ``dimension-bounded'', struggling to generalize across heterogeneous datasets.To bridge this gap, we introduce Unicorn (Universal Correlation Network), a framework for scalable, multi-dataset pretraining on high-dimensional time series. At the core of Unicorn is a latent prototype codebook that decouples correlation modeling from specific channel identities. By pr","authors_text":"Haochen Yuan, Xiaokang Yang, Yichen Song, Yunbo Wang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-26T10:17:09Z","title":"Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30376","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":"sha256:9336f3cb9d0fb9480a491d3e4285c971dfca5823333a74aa807311b76c325650","target":"record","created_at":"2026-06-01T00:02:08Z","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":"e96dd398a0369e04aac7100b4f5ed05b86a4ef36c622bc86edb73a47535461d6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-26T10:17:09Z","title_canon_sha256":"c70ef89aeb3d4874ea6b3aa95f66dd45553862cfa2f74a45bb932632cf130e8a"},"schema_version":"1.0","source":{"id":"2605.30376","kind":"arxiv","version":1}},"canonical_sha256":"1417ac44e8b82211a0f11c7612f48ab082ef85c2d8e8cc0dd50c87dc48b4dc95","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1417ac44e8b82211a0f11c7612f48ab082ef85c2d8e8cc0dd50c87dc48b4dc95","first_computed_at":"2026-06-01T00:02:08.215873Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T00:02:08.215873Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0mCzNOsaN6lGfBJDXBCUa8k6xuLZ4fk1qlz0fpka1ifFpu9GsMsT8jyqax5TOeIoMHI0aOv5+o8FA9FMzcNlBg==","signature_status":"signed_v1","signed_at":"2026-06-01T00:02:08.217004Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30376","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9336f3cb9d0fb9480a491d3e4285c971dfca5823333a74aa807311b76c325650","sha256:f380e80eede6a9a0e581bcc881330da9275d40f9502ed8739e505013ba278fb4"],"state_sha256":"4aa3673d1391b578b6a2d99f54b14f768725a019ad9696a668f6126737af34ec"}