{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IMOBIR2HAVJNCAS42U3W4SWR54","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":"067f115ab3330cb65b068ac4370ae1c9cb59481296956d197b79cd967cb45b5a","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-10-18T06:39:13Z","title_canon_sha256":"6d22d427169cbb5f9aed68e3ff22d9d0fd8a0defe7a7a8747b02227495df69da"},"schema_version":"1.0","source":{"id":"2410.19818","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.19818","created_at":"2026-07-05T09:26:33Z"},{"alias_kind":"arxiv_version","alias_value":"2410.19818v1","created_at":"2026-07-05T09:26:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.19818","created_at":"2026-07-05T09:26:33Z"},{"alias_kind":"pith_short_12","alias_value":"IMOBIR2HAVJN","created_at":"2026-07-05T09:26:33Z"},{"alias_kind":"pith_short_16","alias_value":"IMOBIR2HAVJNCAS4","created_at":"2026-07-05T09:26:33Z"},{"alias_kind":"pith_short_8","alias_value":"IMOBIR2H","created_at":"2026-07-05T09:26:33Z"}],"graph_snapshots":[{"event_id":"sha256:d25acb9ac82d46cedaa4cfc53713a7f89dc39bc808342bdc4e562fa361f4c51d","target":"graph","created_at":"2026-07-05T09:26:33Z","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/2410.19818/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Motion time series collected from mobile and wearable devices such as smartphones and smartwatches offer significant insights into human behavioral patterns, with wide applications in healthcare, automation, IoT, and AR/XR due to their low-power, always-on nature. However, given security and privacy concerns, building large-scale motion time series datasets remains difficult, preventing the development of pre-trained models for human activity analysis. Typically, existing models are trained and tested on the same dataset, leading to poor generalizability across variations in device location, d","authors_text":"Dezhi Hong, Diyan Teng, Jingbo Shang, Rajesh K. Gupta, Ranak Roy Chowdhury, Shuheng Li, Xiyuan Zhang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-10-18T06:39:13Z","title":"UniMTS: Unified Pre-training for Motion Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.19818","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:a77f42e1ef77b0bf314c6b5ce07831f89044d9a2edf5882d144e581593a9a9d8","target":"record","created_at":"2026-07-05T09:26:33Z","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":"067f115ab3330cb65b068ac4370ae1c9cb59481296956d197b79cd967cb45b5a","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-10-18T06:39:13Z","title_canon_sha256":"6d22d427169cbb5f9aed68e3ff22d9d0fd8a0defe7a7a8747b02227495df69da"},"schema_version":"1.0","source":{"id":"2410.19818","kind":"arxiv","version":1}},"canonical_sha256":"431c1447470552d1025cd5376e4ad1ef1bc5d2b1cc68826323bebedfae2ae232","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"431c1447470552d1025cd5376e4ad1ef1bc5d2b1cc68826323bebedfae2ae232","first_computed_at":"2026-07-05T09:26:33.845915Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:26:33.845915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YMQV9tyKENNkeLjVrSWN8wYX4ijlT4uoeVlPY/u3St18YwFkJJw8URUtgK2YsihHn/KXtcQ7e1+WvjZHtAK9Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:26:33.846452Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.19818","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a77f42e1ef77b0bf314c6b5ce07831f89044d9a2edf5882d144e581593a9a9d8","sha256:d25acb9ac82d46cedaa4cfc53713a7f89dc39bc808342bdc4e562fa361f4c51d"],"state_sha256":"93f03d129f409c04ea6562584d20b6f826e30ee77ad56a1016344301e28fdc26"}