{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:3TVS7CJPFWBWSHNGNFGAKPIKE3","short_pith_number":"pith:3TVS7CJP","schema_version":"1.0","canonical_sha256":"dceb2f892f2d83691da6694c053d0a26ce02179d32370c42b9fd28aa65b69468","source":{"kind":"arxiv","id":"2411.11623","version":3},"attestation_state":"computed","paper":{"title":"Federated Incremental Named Entity Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chenxing Li, Dong Yu, Duzhen Zhang, Jiahua Dong, Yahan Yu","submitted_at":"2024-11-18T14:53:53Z","abstract_excerpt":"Federated Named Entity Recognition (FNER) boosts model training within each local client by aggregating the model updates of decentralized local clients, without sharing their private data. However, existing FNER methods assume fixed entity types and local clients in advance, leading to their ineffectiveness in practical applications. In a more realistic scenario, local clients receive new entity types continuously, while new local clients collecting novel data may irregularly join the global FNER training. This challenging setup, referred to here as Federated Incremental NER, renders the glob"},"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":"2411.11623","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-18T14:53:53Z","cross_cats_sorted":[],"title_canon_sha256":"528e377c98960c567a29c4f8e7fa3b0642fb5c1cd69c3784124ce38346497aaa","abstract_canon_sha256":"180d8cbbe6eb451255658d882c481f0bcdcffd0f1ceaea14ed71bac5c78fe224"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:41:17.217024Z","signature_b64":"j7JWy4rFnUp1jzR4JuBNkaPOsmoYMQa5934q1YhIl1ZQxhrUQMXc1Jlf/7Co4AbBFYUohJ0Rx0XEYCmPteE5Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dceb2f892f2d83691da6694c053d0a26ce02179d32370c42b9fd28aa65b69468","last_reissued_at":"2026-07-05T10:41:17.216472Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:41:17.216472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Federated Incremental Named Entity Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chenxing Li, Dong Yu, Duzhen Zhang, Jiahua Dong, Yahan Yu","submitted_at":"2024-11-18T14:53:53Z","abstract_excerpt":"Federated Named Entity Recognition (FNER) boosts model training within each local client by aggregating the model updates of decentralized local clients, without sharing their private data. However, existing FNER methods assume fixed entity types and local clients in advance, leading to their ineffectiveness in practical applications. In a more realistic scenario, local clients receive new entity types continuously, while new local clients collecting novel data may irregularly join the global FNER training. This challenging setup, referred to here as Federated Incremental NER, renders the glob"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.11623","kind":"arxiv","version":3},"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/2411.11623/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":"2411.11623","created_at":"2026-07-05T10:41:17.216532+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.11623v3","created_at":"2026-07-05T10:41:17.216532+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.11623","created_at":"2026-07-05T10:41:17.216532+00:00"},{"alias_kind":"pith_short_12","alias_value":"3TVS7CJPFWBW","created_at":"2026-07-05T10:41:17.216532+00:00"},{"alias_kind":"pith_short_16","alias_value":"3TVS7CJPFWBWSHNG","created_at":"2026-07-05T10:41:17.216532+00:00"},{"alias_kind":"pith_short_8","alias_value":"3TVS7CJP","created_at":"2026-07-05T10:41:17.216532+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/3TVS7CJPFWBWSHNGNFGAKPIKE3","json":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3.json","graph_json":"https://pith.science/api/pith-number/3TVS7CJPFWBWSHNGNFGAKPIKE3/graph.json","events_json":"https://pith.science/api/pith-number/3TVS7CJPFWBWSHNGNFGAKPIKE3/events.json","paper":"https://pith.science/paper/3TVS7CJP"},"agent_actions":{"view_html":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3","download_json":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3.json","view_paper":"https://pith.science/paper/3TVS7CJP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.11623&json=true","fetch_graph":"https://pith.science/api/pith-number/3TVS7CJPFWBWSHNGNFGAKPIKE3/graph.json","fetch_events":"https://pith.science/api/pith-number/3TVS7CJPFWBWSHNGNFGAKPIKE3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3/action/storage_attestation","attest_author":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3/action/author_attestation","sign_citation":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3/action/citation_signature","submit_replication":"https://pith.science/pith/3TVS7CJPFWBWSHNGNFGAKPIKE3/action/replication_record"}},"created_at":"2026-07-05T10:41:17.216532+00:00","updated_at":"2026-07-05T10:41:17.216532+00:00"}