{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:SQV5SEN3CV5C5AJKQ2LMA6U3IB","short_pith_number":"pith:SQV5SEN3","schema_version":"1.0","canonical_sha256":"942bd911bb157a2e812a8696c07a9b4066d231a7ef841c219d9622de2a99312d","source":{"kind":"arxiv","id":"2505.19722","version":1},"attestation_state":"computed","paper":{"title":"Distilling Closed-Source LLM's Knowledge for Locally Stable and Economic Biomedical Entity Linking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Kunpeng Liu, Pengfei Wang, Weiwei Dai, Wenjuan Cui, Yi Du, Yihao Ai, Yuanchun Zhou, Zhiyuan Ning","submitted_at":"2025-05-26T09:10:19Z","abstract_excerpt":"Biomedical entity linking aims to map nonstandard entities to standard entities in a knowledge base. Traditional supervised methods perform well but require extensive annotated data to transfer, limiting their usage in low-resource scenarios. Large language models (LLMs), especially closed-source LLMs, can address these but risk stability issues and high economic costs: using these models is restricted by commercial companies and brings significant economic costs when dealing with large amounts of data. To address this, we propose ``RPDR'', a framework combining closed-source LLMs and open-sou"},"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":"2505.19722","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-05-26T09:10:19Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f3d8ecc1c8a99ddceae9018990b93d14b15af46a2cc2dc864920fd99c12280d8","abstract_canon_sha256":"78e071cc554cd84640bc017b734293b7ed6277ee4a354342f3663110e477e08b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:35.223491Z","signature_b64":"R89YKFrIhWVZqzgkPM7V9X3Vtq03EDZFH2SA+chYDOp7iaNJYkb5L9KpjdfIQE2Iy8oPz6y2h7NTBkROxf7DAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"942bd911bb157a2e812a8696c07a9b4066d231a7ef841c219d9622de2a99312d","last_reissued_at":"2026-07-05T11:09:35.222989Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:35.222989Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distilling Closed-Source LLM's Knowledge for Locally Stable and Economic Biomedical Entity Linking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Kunpeng Liu, Pengfei Wang, Weiwei Dai, Wenjuan Cui, Yi Du, Yihao Ai, Yuanchun Zhou, Zhiyuan Ning","submitted_at":"2025-05-26T09:10:19Z","abstract_excerpt":"Biomedical entity linking aims to map nonstandard entities to standard entities in a knowledge base. Traditional supervised methods perform well but require extensive annotated data to transfer, limiting their usage in low-resource scenarios. Large language models (LLMs), especially closed-source LLMs, can address these but risk stability issues and high economic costs: using these models is restricted by commercial companies and brings significant economic costs when dealing with large amounts of data. To address this, we propose ``RPDR'', a framework combining closed-source LLMs and open-sou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.19722","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/2505.19722/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":"2505.19722","created_at":"2026-07-05T11:09:35.223042+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.19722v1","created_at":"2026-07-05T11:09:35.223042+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.19722","created_at":"2026-07-05T11:09:35.223042+00:00"},{"alias_kind":"pith_short_12","alias_value":"SQV5SEN3CV5C","created_at":"2026-07-05T11:09:35.223042+00:00"},{"alias_kind":"pith_short_16","alias_value":"SQV5SEN3CV5C5AJK","created_at":"2026-07-05T11:09:35.223042+00:00"},{"alias_kind":"pith_short_8","alias_value":"SQV5SEN3","created_at":"2026-07-05T11:09:35.223042+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/SQV5SEN3CV5C5AJKQ2LMA6U3IB","json":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB.json","graph_json":"https://pith.science/api/pith-number/SQV5SEN3CV5C5AJKQ2LMA6U3IB/graph.json","events_json":"https://pith.science/api/pith-number/SQV5SEN3CV5C5AJKQ2LMA6U3IB/events.json","paper":"https://pith.science/paper/SQV5SEN3"},"agent_actions":{"view_html":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB","download_json":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB.json","view_paper":"https://pith.science/paper/SQV5SEN3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.19722&json=true","fetch_graph":"https://pith.science/api/pith-number/SQV5SEN3CV5C5AJKQ2LMA6U3IB/graph.json","fetch_events":"https://pith.science/api/pith-number/SQV5SEN3CV5C5AJKQ2LMA6U3IB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB/action/storage_attestation","attest_author":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB/action/author_attestation","sign_citation":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB/action/citation_signature","submit_replication":"https://pith.science/pith/SQV5SEN3CV5C5AJKQ2LMA6U3IB/action/replication_record"}},"created_at":"2026-07-05T11:09:35.223042+00:00","updated_at":"2026-07-05T11:09:35.223042+00:00"}