{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:7QEU77NRKS3PGQNHQGA3G743JN","short_pith_number":"pith:7QEU77NR","canonical_record":{"source":{"id":"2310.19975","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-30T19:38:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cad2249fb8a6bf5d4d601e6e09bd49c89ac762802810186d899e2f6c1d99fe2e","abstract_canon_sha256":"42f6994f412ddd2b86bcbb5a0c1e2db43d5e52f95a881a9f5c0997e98643dc77"},"schema_version":"1.0"},"canonical_sha256":"fc094ffdb154b6f341a78181b37f9b4b62c0cb543272588babb9cbf0d4b08c40","source":{"kind":"arxiv","id":"2310.19975","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.19975","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"arxiv_version","alias_value":"2310.19975v3","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.19975","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_12","alias_value":"7QEU77NRKS3P","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_16","alias_value":"7QEU77NRKS3PGQNH","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_8","alias_value":"7QEU77NR","created_at":"2026-07-05T08:28:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:7QEU77NRKS3PGQNHQGA3G743JN","target":"record","payload":{"canonical_record":{"source":{"id":"2310.19975","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-30T19:38:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cad2249fb8a6bf5d4d601e6e09bd49c89ac762802810186d899e2f6c1d99fe2e","abstract_canon_sha256":"42f6994f412ddd2b86bcbb5a0c1e2db43d5e52f95a881a9f5c0997e98643dc77"},"schema_version":"1.0"},"canonical_sha256":"fc094ffdb154b6f341a78181b37f9b4b62c0cb543272588babb9cbf0d4b08c40","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:28:34.840872Z","signature_b64":"nLkbsfzFbW2ix8J3LvEIW0Xh/C9f6NviZv7g2RdLAFu9+V1Nlw+ISrE19UdrE/Bzta54mmCQyGcUruWGWlhhAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc094ffdb154b6f341a78181b37f9b4b62c0cb543272588babb9cbf0d4b08c40","last_reissued_at":"2026-07-05T08:28:34.840463Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:28:34.840463Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.19975","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:28:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MZldjbv+4wGrfeWM1IbkuQvABRKPZzy/yEyfWFhCCF6DXpzuXDlook9PkGLE/GyOgyRkPB6lUiXgTUy5aCJXBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T22:39:57.812949Z"},"content_sha256":"0ba5997cf2bbd6b50dba941cf9fc2a70a635cacfd24c06bfdf2fc1129c117d99","schema_version":"1.0","event_id":"sha256:0ba5997cf2bbd6b50dba941cf9fc2a70a635cacfd24c06bfdf2fc1129c117d99"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:7QEU77NRKS3PGQNHQGA3G743JN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Hieu Tran, Hong Yu, Zhichao Yang, Zonghai Yao","submitted_at":"2023-10-30T19:38:50Z","abstract_excerpt":"To enhance the performance of large language models (LLMs) in biomedical natural language processing (BioNLP) by introducing a domain-specific instruction dataset and examining its impact when combined with multi-task learning principles. We created the BioInstruct, comprising 25,005 instructions to instruction-tune LLMs(LLaMA 1 & 2, 7B & 13B version). The instructions were created by prompting the GPT-4 language model with three-seed samples randomly drawn from an 80 human curated instructions. We employed Low-Rank Adaptation(LoRA) for parameter-efficient fine-tuning. We then evaluated these "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.19975","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/2310.19975/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:28:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"msmmZFLU2uwPDaSQxxbkyNb/xjNSIk1ENi8EDcT8nOeVwvDNJoNtHKoc+dPS7+zrMG0CLoJqDBdg8qVPwTdPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T22:39:57.813468Z"},"content_sha256":"5889098f4b1159883098632b64ab17710f5416cb104eca27100a0123f52c0228","schema_version":"1.0","event_id":"sha256:5889098f4b1159883098632b64ab17710f5416cb104eca27100a0123f52c0228"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7QEU77NRKS3PGQNHQGA3G743JN/bundle.json","state_url":"https://pith.science/pith/7QEU77NRKS3PGQNHQGA3G743JN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7QEU77NRKS3PGQNHQGA3G743JN/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-20T22:39:57Z","links":{"resolver":"https://pith.science/pith/7QEU77NRKS3PGQNHQGA3G743JN","bundle":"https://pith.science/pith/7QEU77NRKS3PGQNHQGA3G743JN/bundle.json","state":"https://pith.science/pith/7QEU77NRKS3PGQNHQGA3G743JN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7QEU77NRKS3PGQNHQGA3G743JN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7QEU77NRKS3PGQNHQGA3G743JN","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":"42f6994f412ddd2b86bcbb5a0c1e2db43d5e52f95a881a9f5c0997e98643dc77","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-30T19:38:50Z","title_canon_sha256":"cad2249fb8a6bf5d4d601e6e09bd49c89ac762802810186d899e2f6c1d99fe2e"},"schema_version":"1.0","source":{"id":"2310.19975","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.19975","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"arxiv_version","alias_value":"2310.19975v3","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.19975","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_12","alias_value":"7QEU77NRKS3P","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_16","alias_value":"7QEU77NRKS3PGQNH","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_8","alias_value":"7QEU77NR","created_at":"2026-07-05T08:28:34Z"}],"graph_snapshots":[{"event_id":"sha256:5889098f4b1159883098632b64ab17710f5416cb104eca27100a0123f52c0228","target":"graph","created_at":"2026-07-05T08:28:34Z","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/2310.19975/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To enhance the performance of large language models (LLMs) in biomedical natural language processing (BioNLP) by introducing a domain-specific instruction dataset and examining its impact when combined with multi-task learning principles. We created the BioInstruct, comprising 25,005 instructions to instruction-tune LLMs(LLaMA 1 & 2, 7B & 13B version). The instructions were created by prompting the GPT-4 language model with three-seed samples randomly drawn from an 80 human curated instructions. We employed Low-Rank Adaptation(LoRA) for parameter-efficient fine-tuning. We then evaluated these ","authors_text":"Hieu Tran, Hong Yu, Zhichao Yang, Zonghai Yao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-30T19:38:50Z","title":"BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.19975","kind":"arxiv","version":3},"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":"sha256:0ba5997cf2bbd6b50dba941cf9fc2a70a635cacfd24c06bfdf2fc1129c117d99","target":"record","created_at":"2026-07-05T08:28:34Z","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":"42f6994f412ddd2b86bcbb5a0c1e2db43d5e52f95a881a9f5c0997e98643dc77","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-30T19:38:50Z","title_canon_sha256":"cad2249fb8a6bf5d4d601e6e09bd49c89ac762802810186d899e2f6c1d99fe2e"},"schema_version":"1.0","source":{"id":"2310.19975","kind":"arxiv","version":3}},"canonical_sha256":"fc094ffdb154b6f341a78181b37f9b4b62c0cb543272588babb9cbf0d4b08c40","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fc094ffdb154b6f341a78181b37f9b4b62c0cb543272588babb9cbf0d4b08c40","first_computed_at":"2026-07-05T08:28:34.840463Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:28:34.840463Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nLkbsfzFbW2ix8J3LvEIW0Xh/C9f6NviZv7g2RdLAFu9+V1Nlw+ISrE19UdrE/Bzta54mmCQyGcUruWGWlhhAg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:28:34.840872Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.19975","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ba5997cf2bbd6b50dba941cf9fc2a70a635cacfd24c06bfdf2fc1129c117d99","sha256:5889098f4b1159883098632b64ab17710f5416cb104eca27100a0123f52c0228"],"state_sha256":"7537dcd08e913c19500ae185051169a34c6f600e4d1266ea438f61a03520f91d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l7re0gO+SzV6db69ReEcBG2g/FVcCx23bUayMoc7GmnbPa0nICpVNCJmTPr7GYlIPkzz66FCUPlD76vKGVK/DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T22:39:57.817338Z","bundle_sha256":"66aa42b453fbc37c480c0350a2d1f6ba6d5d9c7ec63ecef1bc4a45dbcfd78258"}}