{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VXYWTEWXUVEP4TJGLR5TJVTL6T","short_pith_number":"pith:VXYWTEWX","schema_version":"1.0","canonical_sha256":"adf16992d7a548fe4d265c7b34d66bf4da06ec139bdd538c16f9ad1c142091ca","source":{"kind":"arxiv","id":"2605.20628","version":1},"attestation_state":"computed","paper":{"title":"Divide-Prompt-Refine: a Training-Free, Structure-Aware Framework for Biomedical Abstract Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dongin Nam, Halil Kilicoglu, Joe Menke, Neil Smalheiser, Shufan Ming, Sylvey Lin","submitted_at":"2026-05-20T02:25:21Z","abstract_excerpt":"Biomedical abstracts play a critical role in downstream NLP applications, such as information retrieval, biocuration, and biomedical knowledge discovery. However, a non-trivial number of biomedical articles do not have abstracts, diminishing the utility of these articles for downstream tasks. We propose DPR-BAG (Divide, Prompt, and Refine for Biomedical Abstract Generation), a training-free, zero-shot framework that generates coherent and factually grounded abstracts for biomedical articles with full text but no abstract. DPR-BAG decomposes full-text documents into structured rhetorical facets"},"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":"2605.20628","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-20T02:25:21Z","cross_cats_sorted":[],"title_canon_sha256":"6a15a82c64b4f3c09107387545b05cd6582ed095e3de5e0a3e71a88b36761f96","abstract_canon_sha256":"31ea09e09f15dd31fbb63f73d1edf76b9a2549546afa518949e84ba1b8a22a15"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T01:04:45.627779Z","signature_b64":"NwQBjbNC8NoI0XEyrk7U2IeXEjauMGTnEawaAsR4Bf7Z0o9ONeXzYBJwlpL+ynUC4NqeGk4QqSOkCehZ/dVMCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"adf16992d7a548fe4d265c7b34d66bf4da06ec139bdd538c16f9ad1c142091ca","last_reissued_at":"2026-05-21T01:04:45.627168Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T01:04:45.627168Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Divide-Prompt-Refine: a Training-Free, Structure-Aware Framework for Biomedical Abstract Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dongin Nam, Halil Kilicoglu, Joe Menke, Neil Smalheiser, Shufan Ming, Sylvey Lin","submitted_at":"2026-05-20T02:25:21Z","abstract_excerpt":"Biomedical abstracts play a critical role in downstream NLP applications, such as information retrieval, biocuration, and biomedical knowledge discovery. However, a non-trivial number of biomedical articles do not have abstracts, diminishing the utility of these articles for downstream tasks. We propose DPR-BAG (Divide, Prompt, and Refine for Biomedical Abstract Generation), a training-free, zero-shot framework that generates coherent and factually grounded abstracts for biomedical articles with full text but no abstract. DPR-BAG decomposes full-text documents into structured rhetorical facets"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20628","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/2605.20628/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":"2605.20628","created_at":"2026-05-21T01:04:45.627295+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.20628v1","created_at":"2026-05-21T01:04:45.627295+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20628","created_at":"2026-05-21T01:04:45.627295+00:00"},{"alias_kind":"pith_short_12","alias_value":"VXYWTEWXUVEP","created_at":"2026-05-21T01:04:45.627295+00:00"},{"alias_kind":"pith_short_16","alias_value":"VXYWTEWXUVEP4TJG","created_at":"2026-05-21T01:04:45.627295+00:00"},{"alias_kind":"pith_short_8","alias_value":"VXYWTEWX","created_at":"2026-05-21T01:04:45.627295+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/VXYWTEWXUVEP4TJGLR5TJVTL6T","json":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T.json","graph_json":"https://pith.science/api/pith-number/VXYWTEWXUVEP4TJGLR5TJVTL6T/graph.json","events_json":"https://pith.science/api/pith-number/VXYWTEWXUVEP4TJGLR5TJVTL6T/events.json","paper":"https://pith.science/paper/VXYWTEWX"},"agent_actions":{"view_html":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T","download_json":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T.json","view_paper":"https://pith.science/paper/VXYWTEWX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.20628&json=true","fetch_graph":"https://pith.science/api/pith-number/VXYWTEWXUVEP4TJGLR5TJVTL6T/graph.json","fetch_events":"https://pith.science/api/pith-number/VXYWTEWXUVEP4TJGLR5TJVTL6T/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T/action/storage_attestation","attest_author":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T/action/author_attestation","sign_citation":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T/action/citation_signature","submit_replication":"https://pith.science/pith/VXYWTEWXUVEP4TJGLR5TJVTL6T/action/replication_record"}},"created_at":"2026-05-21T01:04:45.627295+00:00","updated_at":"2026-05-21T01:04:45.627295+00:00"}