{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IXFYRHAWH4Q567SMB4BEU4BDPH","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":"489076dac824958bc299ee1a4e298ed7ae90da311ea5e7d14ac1b2b8d6839f46","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-15T12:39:20Z","title_canon_sha256":"5cde90281d3d5b2b0d3b06dec5c86487e06372fde615842cf9e7c2a0721f2c70"},"schema_version":"1.0","source":{"id":"2410.11550","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.11550","created_at":"2026-07-05T09:20:55Z"},{"alias_kind":"arxiv_version","alias_value":"2410.11550v1","created_at":"2026-07-05T09:20:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.11550","created_at":"2026-07-05T09:20:55Z"},{"alias_kind":"pith_short_12","alias_value":"IXFYRHAWH4Q5","created_at":"2026-07-05T09:20:55Z"},{"alias_kind":"pith_short_16","alias_value":"IXFYRHAWH4Q567SM","created_at":"2026-07-05T09:20:55Z"},{"alias_kind":"pith_short_8","alias_value":"IXFYRHAW","created_at":"2026-07-05T09:20:55Z"}],"graph_snapshots":[{"event_id":"sha256:8357d4c96a8aec064c720745c5b572e5806d0cc532bb7d82ddb1a2629ce2bda7","target":"graph","created_at":"2026-07-05T09:20:55Z","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/2410.11550/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have recently demonstrated remarkable performance in general tasks across various fields. However, their effectiveness within specific domains such as drug development remains challenges. To solve these challenges, we introduce \\textbf{Y-Mol}, forming a well-established LLM paradigm for the flow of drug development. Y-Mol is a multiscale biomedical knowledge-guided LLM designed to accomplish tasks across lead compound discovery, pre-clinic, and clinic prediction. By integrating millions of multiscale biomedical knowledge and using LLaMA2 as the base LLM, Y-Mol augm","authors_text":"Chaoyi Li, Daojian Zeng, Dongsheng Cao, Long Chen, Peng Zhou, Tengfei Ma, Tianle Li, Xiangxiang Zeng, Xibao Cai, Xinyu Yang, Xuan Lin","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-15T12:39:20Z","title":"Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.11550","kind":"arxiv","version":1},"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":"sha256:75274ffdcfae765485f62c53d55b68951f0bee089030a020afb6aed6d87c5d0e","target":"record","created_at":"2026-07-05T09:20:55Z","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":"489076dac824958bc299ee1a4e298ed7ae90da311ea5e7d14ac1b2b8d6839f46","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-15T12:39:20Z","title_canon_sha256":"5cde90281d3d5b2b0d3b06dec5c86487e06372fde615842cf9e7c2a0721f2c70"},"schema_version":"1.0","source":{"id":"2410.11550","kind":"arxiv","version":1}},"canonical_sha256":"45cb889c163f21df7e4c0f024a702379da91661ac2b53f046cefe43922f1a0aa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"45cb889c163f21df7e4c0f024a702379da91661ac2b53f046cefe43922f1a0aa","first_computed_at":"2026-07-05T09:20:55.530595Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:20:55.530595Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mL0ARIvUqTy3dnjbTYKnPjMRa1rQV+A/P7wrDWUFicGldH3qITFRnFu4eInhsC4Qa5qE6b4G+ZsrXuTPV6XrDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:20:55.531093Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.11550","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75274ffdcfae765485f62c53d55b68951f0bee089030a020afb6aed6d87c5d0e","sha256:8357d4c96a8aec064c720745c5b572e5806d0cc532bb7d82ddb1a2629ce2bda7"],"state_sha256":"52c1de08dd101ba4803f462121656928f0ef8e090339a2c9625990371d881f7e"}