{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:H2HE3IXPUTHQNGX2U3KCA2E2TT","short_pith_number":"pith:H2HE3IXP","canonical_record":{"source":{"id":"2408.13378","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-08-23T21:24:59Z","cross_cats_sorted":["cs.CL","cs.IR","cs.LG","q-bio.QM"],"title_canon_sha256":"fef77c90bbfa46656384096bef7447ff2666404d922003d706039e7366b626b8","abstract_canon_sha256":"1993990aaf5d2d22178113a1ff10b142aae1e58b59f1fa172c6499e94daaa69d"},"schema_version":"1.0"},"canonical_sha256":"3e8e4da2efa4cf069afaa6d420689a9cf7d4f24b1592afd5a63b9fbe422d1d3a","source":{"kind":"arxiv","id":"2408.13378","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.13378","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"2408.13378v4","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.13378","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"H2HE3IXPUTHQ","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_16","alias_value":"H2HE3IXPUTHQNGX2","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_8","alias_value":"H2HE3IXP","created_at":"2026-07-05T10:45:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:H2HE3IXPUTHQNGX2U3KCA2E2TT","target":"record","payload":{"canonical_record":{"source":{"id":"2408.13378","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-08-23T21:24:59Z","cross_cats_sorted":["cs.CL","cs.IR","cs.LG","q-bio.QM"],"title_canon_sha256":"fef77c90bbfa46656384096bef7447ff2666404d922003d706039e7366b626b8","abstract_canon_sha256":"1993990aaf5d2d22178113a1ff10b142aae1e58b59f1fa172c6499e94daaa69d"},"schema_version":"1.0"},"canonical_sha256":"3e8e4da2efa4cf069afaa6d420689a9cf7d4f24b1592afd5a63b9fbe422d1d3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:45:38.079134Z","signature_b64":"gDHD5e7H7UZLoTNA4Ptw9eBcJ4lNzYou29+77uO12kD/Zc7j9tj5cgZ0njL5hyvmlD1j5e/VXaGQxSmwCODeBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e8e4da2efa4cf069afaa6d420689a9cf7d4f24b1592afd5a63b9fbe422d1d3a","last_reissued_at":"2026-07-05T10:45:38.078645Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:45:38.078645Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.13378","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9MRErhhb6ZJ0e60oPViwDu0QZFlTw0ymmYWiU3BBCUelzVH4E9Q5bfgITohCfoXJCNhQ3dzaNnM1mTE1V21/BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:02:04.208058Z"},"content_sha256":"e0a1de2170f1948266b58250f5ac487dac6c8f07127f719de29e10e83d89db15","schema_version":"1.0","event_id":"sha256:e0a1de2170f1948266b58250f5ac487dac6c8f07127f719de29e10e83d89db15"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:H2HE3IXPUTHQNGX2U3KCA2E2TT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DrugAgent: Multi-Agent Large Language Model-Based Reasoning for Drug-Target Interaction Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.IR","cs.LG","q-bio.QM"],"primary_cat":"cs.AI","authors_text":"Augustin Luna, Tianci Song, Tianfan Fu, Xinling Wang, Yoshitaka Inoue","submitted_at":"2024-08-23T21:24:59Z","abstract_excerpt":"Advancements in large language models (LLMs) allow them to address diverse questions using human-like interfaces. Still, limitations in their training prevent them from answering accurately in scenarios that could benefit from multiple perspectives. Multi-agent systems allow the resolution of questions to enhance result consistency and reliability. While drug-target interaction (DTI) prediction is important for drug discovery, existing approaches face challenges due to complex biological systems and the lack of interpretability needed for clinical applications. DrugAgent is a multi-agent LLM s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.13378","kind":"arxiv","version":4},"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/2408.13378/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":"2026-07-05T10:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gl3/vfGPiYM++BPwkgFt3sER/osdqjTSEelJ+KPmTroYvQhDX8osab7TrjNCvCaB+BD7bKKkTWnMoyO//hEAAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:02:04.208981Z"},"content_sha256":"ef8a81afa67713d014f4c82932a73ce7f5257e6b5a68fb0b522d2f312f395cb7","schema_version":"1.0","event_id":"sha256:ef8a81afa67713d014f4c82932a73ce7f5257e6b5a68fb0b522d2f312f395cb7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H2HE3IXPUTHQNGX2U3KCA2E2TT/bundle.json","state_url":"https://pith.science/pith/H2HE3IXPUTHQNGX2U3KCA2E2TT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H2HE3IXPUTHQNGX2U3KCA2E2TT/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":"2026-08-05T18:02:04Z","links":{"resolver":"https://pith.science/pith/H2HE3IXPUTHQNGX2U3KCA2E2TT","bundle":"https://pith.science/pith/H2HE3IXPUTHQNGX2U3KCA2E2TT/bundle.json","state":"https://pith.science/pith/H2HE3IXPUTHQNGX2U3KCA2E2TT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H2HE3IXPUTHQNGX2U3KCA2E2TT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:H2HE3IXPUTHQNGX2U3KCA2E2TT","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":"1993990aaf5d2d22178113a1ff10b142aae1e58b59f1fa172c6499e94daaa69d","cross_cats_sorted":["cs.CL","cs.IR","cs.LG","q-bio.QM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-08-23T21:24:59Z","title_canon_sha256":"fef77c90bbfa46656384096bef7447ff2666404d922003d706039e7366b626b8"},"schema_version":"1.0","source":{"id":"2408.13378","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.13378","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"2408.13378v4","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.13378","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"H2HE3IXPUTHQ","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_16","alias_value":"H2HE3IXPUTHQNGX2","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_8","alias_value":"H2HE3IXP","created_at":"2026-07-05T10:45:38Z"}],"graph_snapshots":[{"event_id":"sha256:ef8a81afa67713d014f4c82932a73ce7f5257e6b5a68fb0b522d2f312f395cb7","target":"graph","created_at":"2026-07-05T10:45:38Z","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/2408.13378/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Advancements in large language models (LLMs) allow them to address diverse questions using human-like interfaces. Still, limitations in their training prevent them from answering accurately in scenarios that could benefit from multiple perspectives. Multi-agent systems allow the resolution of questions to enhance result consistency and reliability. While drug-target interaction (DTI) prediction is important for drug discovery, existing approaches face challenges due to complex biological systems and the lack of interpretability needed for clinical applications. DrugAgent is a multi-agent LLM s","authors_text":"Augustin Luna, Tianci Song, Tianfan Fu, Xinling Wang, Yoshitaka Inoue","cross_cats":["cs.CL","cs.IR","cs.LG","q-bio.QM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-08-23T21:24:59Z","title":"DrugAgent: Multi-Agent Large Language Model-Based Reasoning for Drug-Target Interaction Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.13378","kind":"arxiv","version":4},"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:e0a1de2170f1948266b58250f5ac487dac6c8f07127f719de29e10e83d89db15","target":"record","created_at":"2026-07-05T10:45:38Z","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":"1993990aaf5d2d22178113a1ff10b142aae1e58b59f1fa172c6499e94daaa69d","cross_cats_sorted":["cs.CL","cs.IR","cs.LG","q-bio.QM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-08-23T21:24:59Z","title_canon_sha256":"fef77c90bbfa46656384096bef7447ff2666404d922003d706039e7366b626b8"},"schema_version":"1.0","source":{"id":"2408.13378","kind":"arxiv","version":4}},"canonical_sha256":"3e8e4da2efa4cf069afaa6d420689a9cf7d4f24b1592afd5a63b9fbe422d1d3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e8e4da2efa4cf069afaa6d420689a9cf7d4f24b1592afd5a63b9fbe422d1d3a","first_computed_at":"2026-07-05T10:45:38.078645Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:45:38.078645Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gDHD5e7H7UZLoTNA4Ptw9eBcJ4lNzYou29+77uO12kD/Zc7j9tj5cgZ0njL5hyvmlD1j5e/VXaGQxSmwCODeBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:45:38.079134Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.13378","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0a1de2170f1948266b58250f5ac487dac6c8f07127f719de29e10e83d89db15","sha256:ef8a81afa67713d014f4c82932a73ce7f5257e6b5a68fb0b522d2f312f395cb7"],"state_sha256":"ac40f34fcb4a79db3b2f1a25c82dee5282479502077fd83f671cb4bb916f455d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pCtgFPCIzPHqMpLLHq3PAyapZOch4UqkrM9yIFFJp81a6MHStcvOggW6iIdBwsARGWossqmiQyhQQLXrtuPeAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T18:02:04.214474Z","bundle_sha256":"ef8246dce06b4deb81c78cc5067b52084da415ec9c705a9227d218e581bf50ce"}}