{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KDGVPITI7BR6ZC2FQA4HFVDM4T","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":"01246e968424a84cc09f712d72c837f1fd779c2faa736b117551bfdeb0d98ef5","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-07-10T20:32:50Z","title_canon_sha256":"3782695e45c7e012df8dcb33ebb9aa9f38468cb1c253c02b09b5518fe164e245"},"schema_version":"1.0","source":{"id":"2407.08035","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.08035","created_at":"2026-06-11T01:09:08Z"},{"alias_kind":"arxiv_version","alias_value":"2407.08035v2","created_at":"2026-06-11T01:09:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.08035","created_at":"2026-06-11T01:09:08Z"},{"alias_kind":"pith_short_12","alias_value":"KDGVPITI7BR6","created_at":"2026-06-11T01:09:08Z"},{"alias_kind":"pith_short_16","alias_value":"KDGVPITI7BR6ZC2F","created_at":"2026-06-11T01:09:08Z"},{"alias_kind":"pith_short_8","alias_value":"KDGVPITI","created_at":"2026-06-11T01:09:08Z"}],"graph_snapshots":[{"event_id":"sha256:98600dc57e7d21405ba244c19111a4f1d1cd9bbc066dfd5327b921753ebef416","target":"graph","created_at":"2026-06-11T01:09:08Z","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/2407.08035/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have provided a new pathway for Named Entity Recognition (NER) tasks. Compared with fine-tuning, LLM-powered prompting methods avoid the need for training, conserve substantial computational resources, and rely on minimal annotated data. Previous studies have achieved comparable performance to fully supervised BERT-based fine-tuning approaches on general NER benchmarks. However, none of the previous approaches has investigated the efficiency of LLM-based few-shot learning in domain-specific scenarios. To address this gap, we introduce FsPONER, a novel approach for ","authors_text":"Rakebul Hasan, Thomas Runkler, Yongjian Tang","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-07-10T20:32:50Z","title":"FsPONER: Few-shot Prompt Optimization for Named Entity Recognition in Domain-specific Scenarios"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.08035","kind":"arxiv","version":2},"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:e8a4a849c68c99796437d67196b54d40713828a35657f442fdb7fb73a701309e","target":"record","created_at":"2026-06-11T01:09:08Z","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":"01246e968424a84cc09f712d72c837f1fd779c2faa736b117551bfdeb0d98ef5","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-07-10T20:32:50Z","title_canon_sha256":"3782695e45c7e012df8dcb33ebb9aa9f38468cb1c253c02b09b5518fe164e245"},"schema_version":"1.0","source":{"id":"2407.08035","kind":"arxiv","version":2}},"canonical_sha256":"50cd57a268f863ec8b45803872d46ce4ee2d1e3ac5c747cf486c994ceb4c7b24","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"50cd57a268f863ec8b45803872d46ce4ee2d1e3ac5c747cf486c994ceb4c7b24","first_computed_at":"2026-06-11T01:09:08.707915Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-11T01:09:08.707915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uRYsIh7BwnteMlocHZlQYCwSl+knXLaPCOYaK1TTveD7TkC8x+5z3ixPcuMRDUlSqFSgJqkldbL6qE2TCPmEDg==","signature_status":"signed_v1","signed_at":"2026-06-11T01:09:08.708959Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.08035","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e8a4a849c68c99796437d67196b54d40713828a35657f442fdb7fb73a701309e","sha256:98600dc57e7d21405ba244c19111a4f1d1cd9bbc066dfd5327b921753ebef416"],"state_sha256":"db601104c3dfc844ffafe5eab82715d1113b8f6c690e5389a6a2c7bbf9037431"}