{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ANXUHUASVUI5GMU2WAUHE2VHT4","short_pith_number":"pith:ANXUHUAS","schema_version":"1.0","canonical_sha256":"036f43d012ad11d3329ab028726aa79f1218cdc296da0ffbbb8847adddf28655","source":{"kind":"arxiv","id":"2411.17785","version":1},"attestation_state":"computed","paper":{"title":"New Test-Time Scenario for Biosignal: Concept and Its Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"Beom Joon Kim, Byeong Tak Lee, Hak Seung Lee, Jeong-Ho Hong, Joon-myoung Kwon, Yong-yeon Jo","submitted_at":"2024-11-26T14:54:02Z","abstract_excerpt":"Online Test-Time Adaptation (OTTA) enhances model robustness by updating pre-trained models with unlabeled data during testing. In healthcare, OTTA is vital for real-time tasks like predicting blood pressure from biosignals, which demand continuous adaptation. We introduce a new test-time scenario with streams of unlabeled samples and occasional labeled samples. Our framework combines supervised and self-supervised learning, employing a dual-queue buffer and weighted batch sampling to balance data types. Experiments show improved accuracy and adaptability under real-world conditions."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2411.17785","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2024-11-26T14:54:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"03a8bdd5e63a56927ea7c1dbfb621ace94e60a4530d1847f94f3b2c652c3f9d2","abstract_canon_sha256":"3a98db6b02adb7bfbad96be5f580c9891eb362e6efcccdb2be2ba81688d7b8f5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:41:06.793887Z","signature_b64":"CmuoxR3qFUJ2eHzw813xPYRVsL+WZUhWF6yg4QaIrcLFERwVgV+m2TrJ+/yFHeFpbBGLr2PYMaoqxsSYIm8lBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"036f43d012ad11d3329ab028726aa79f1218cdc296da0ffbbb8847adddf28655","last_reissued_at":"2026-07-05T09:41:06.793309Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:41:06.793309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"New Test-Time Scenario for Biosignal: Concept and Its Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"Beom Joon Kim, Byeong Tak Lee, Hak Seung Lee, Jeong-Ho Hong, Joon-myoung Kwon, Yong-yeon Jo","submitted_at":"2024-11-26T14:54:02Z","abstract_excerpt":"Online Test-Time Adaptation (OTTA) enhances model robustness by updating pre-trained models with unlabeled data during testing. In healthcare, OTTA is vital for real-time tasks like predicting blood pressure from biosignals, which demand continuous adaptation. We introduce a new test-time scenario with streams of unlabeled samples and occasional labeled samples. Our framework combines supervised and self-supervised learning, employing a dual-queue buffer and weighted batch sampling to balance data types. Experiments show improved accuracy and adaptability under real-world conditions."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.17785","kind":"arxiv","version":1},"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/2411.17785/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2411.17785","created_at":"2026-07-05T09:41:06.793402+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.17785v1","created_at":"2026-07-05T09:41:06.793402+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.17785","created_at":"2026-07-05T09:41:06.793402+00:00"},{"alias_kind":"pith_short_12","alias_value":"ANXUHUASVUI5","created_at":"2026-07-05T09:41:06.793402+00:00"},{"alias_kind":"pith_short_16","alias_value":"ANXUHUASVUI5GMU2","created_at":"2026-07-05T09:41:06.793402+00:00"},{"alias_kind":"pith_short_8","alias_value":"ANXUHUAS","created_at":"2026-07-05T09:41:06.793402+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4","json":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4.json","graph_json":"https://pith.science/api/pith-number/ANXUHUASVUI5GMU2WAUHE2VHT4/graph.json","events_json":"https://pith.science/api/pith-number/ANXUHUASVUI5GMU2WAUHE2VHT4/events.json","paper":"https://pith.science/paper/ANXUHUAS"},"agent_actions":{"view_html":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4","download_json":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4.json","view_paper":"https://pith.science/paper/ANXUHUAS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.17785&json=true","fetch_graph":"https://pith.science/api/pith-number/ANXUHUASVUI5GMU2WAUHE2VHT4/graph.json","fetch_events":"https://pith.science/api/pith-number/ANXUHUASVUI5GMU2WAUHE2VHT4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4/action/storage_attestation","attest_author":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4/action/author_attestation","sign_citation":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4/action/citation_signature","submit_replication":"https://pith.science/pith/ANXUHUASVUI5GMU2WAUHE2VHT4/action/replication_record"}},"created_at":"2026-07-05T09:41:06.793402+00:00","updated_at":"2026-07-05T09:41:06.793402+00:00"}