{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:JCSCN6WJOBZMBSGVGZDIFKBAMV","short_pith_number":"pith:JCSCN6WJ","schema_version":"1.0","canonical_sha256":"48a426fac97072c0c8d5364682a8206571db24a5acd00b26270f5cdb6a6c0a5a","source":{"kind":"arxiv","id":"2410.18378","version":1},"attestation_state":"computed","paper":{"title":"Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chen Gong, Fan Wu, Guihai Chen, Xiaofeng Jia, Zhenzhe Zheng","submitted_at":"2024-10-24T02:38:09Z","abstract_excerpt":"In modern mobile applications, users frequently encounter various new contexts, necessitating on-device continual learning (CL) to ensure consistent model performance. While existing research predominantly focused on developing lightweight CL frameworks, we identify that data scarcity is a critical bottleneck for on-device CL. In this work, we explore the potential of leveraging abundant cloud-side data to enrich scarce on-device data, and propose a private, efficient and effective data enrichment framework Delta. Specifically, Delta first introduces a directory dataset to decompose the data e"},"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":"2410.18378","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-24T02:38:09Z","cross_cats_sorted":[],"title_canon_sha256":"0cad538ae170d8cd69f14ee5b41d6983743616bc185c9736d6e2d98c6d2643bb","abstract_canon_sha256":"c333a55c6305a4ea68744b9bebc63f9e2baaae4a65d3f5ae98b8ea1713de8e56"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:25:07.449051Z","signature_b64":"0w3v1UDBd0dF67EqrxzXst4uI/C1vwVcZlYH2XXjKL0inO6KYCrNPnzlYGwI78g0oqwjVec7HNJGsqxPKYYhDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"48a426fac97072c0c8d5364682a8206571db24a5acd00b26270f5cdb6a6c0a5a","last_reissued_at":"2026-07-05T09:25:07.448557Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:25:07.448557Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chen Gong, Fan Wu, Guihai Chen, Xiaofeng Jia, Zhenzhe Zheng","submitted_at":"2024-10-24T02:38:09Z","abstract_excerpt":"In modern mobile applications, users frequently encounter various new contexts, necessitating on-device continual learning (CL) to ensure consistent model performance. While existing research predominantly focused on developing lightweight CL frameworks, we identify that data scarcity is a critical bottleneck for on-device CL. In this work, we explore the potential of leveraging abundant cloud-side data to enrich scarce on-device data, and propose a private, efficient and effective data enrichment framework Delta. Specifically, Delta first introduces a directory dataset to decompose the data e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.18378","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/2410.18378/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":"2410.18378","created_at":"2026-07-05T09:25:07.448613+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.18378v1","created_at":"2026-07-05T09:25:07.448613+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.18378","created_at":"2026-07-05T09:25:07.448613+00:00"},{"alias_kind":"pith_short_12","alias_value":"JCSCN6WJOBZM","created_at":"2026-07-05T09:25:07.448613+00:00"},{"alias_kind":"pith_short_16","alias_value":"JCSCN6WJOBZMBSGV","created_at":"2026-07-05T09:25:07.448613+00:00"},{"alias_kind":"pith_short_8","alias_value":"JCSCN6WJ","created_at":"2026-07-05T09:25:07.448613+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/JCSCN6WJOBZMBSGVGZDIFKBAMV","json":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV.json","graph_json":"https://pith.science/api/pith-number/JCSCN6WJOBZMBSGVGZDIFKBAMV/graph.json","events_json":"https://pith.science/api/pith-number/JCSCN6WJOBZMBSGVGZDIFKBAMV/events.json","paper":"https://pith.science/paper/JCSCN6WJ"},"agent_actions":{"view_html":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV","download_json":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV.json","view_paper":"https://pith.science/paper/JCSCN6WJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.18378&json=true","fetch_graph":"https://pith.science/api/pith-number/JCSCN6WJOBZMBSGVGZDIFKBAMV/graph.json","fetch_events":"https://pith.science/api/pith-number/JCSCN6WJOBZMBSGVGZDIFKBAMV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV/action/storage_attestation","attest_author":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV/action/author_attestation","sign_citation":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV/action/citation_signature","submit_replication":"https://pith.science/pith/JCSCN6WJOBZMBSGVGZDIFKBAMV/action/replication_record"}},"created_at":"2026-07-05T09:25:07.448613+00:00","updated_at":"2026-07-05T09:25:07.448613+00:00"}