{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:LCN3AL6DS6VVF2UXHVAA3IZBRV","short_pith_number":"pith:LCN3AL6D","canonical_record":{"source":{"id":"2404.14777","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T06:30:53Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9e338a7e9348df7b6707351f1ddce7cec231f37e79eb3523eccf67aed89c796e","abstract_canon_sha256":"f07dedb1109c79f27acb774896232221bb687707b71ec2d13f5ca0f79693e512"},"schema_version":"1.0"},"canonical_sha256":"589bb02fc397ab52ea973d400da3218d7651254ddef83ff50719c43a77f77824","source":{"kind":"arxiv","id":"2404.14777","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.14777","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"arxiv_version","alias_value":"2404.14777v2","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.14777","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"pith_short_12","alias_value":"LCN3AL6DS6VV","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"pith_short_16","alias_value":"LCN3AL6DS6VVF2UX","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"pith_short_8","alias_value":"LCN3AL6D","created_at":"2026-07-05T08:46:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:LCN3AL6DS6VVF2UXHVAA3IZBRV","target":"record","payload":{"canonical_record":{"source":{"id":"2404.14777","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T06:30:53Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9e338a7e9348df7b6707351f1ddce7cec231f37e79eb3523eccf67aed89c796e","abstract_canon_sha256":"f07dedb1109c79f27acb774896232221bb687707b71ec2d13f5ca0f79693e512"},"schema_version":"1.0"},"canonical_sha256":"589bb02fc397ab52ea973d400da3218d7651254ddef83ff50719c43a77f77824","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:46:24.360828Z","signature_b64":"9YADHWwpIt6fL6rp+Dz7XXfg1zw00C0aBkPfCY6mT51p3ppPqVpbI4HkUnaLJqWXtEpDgguqMOCO0IlJhRZsDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"589bb02fc397ab52ea973d400da3218d7651254ddef83ff50719c43a77f77824","last_reissued_at":"2026-07-05T08:46:24.360312Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:46:24.360312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.14777","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:46:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f0ICzeYSFjNSZsBtPVPNkcETZImK/e9uUd1VdlfTsG6tizX78n9sw4ggHhrci8Yn/+OGixejXFsETk2n1YsaDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T07:21:18.848370Z"},"content_sha256":"81cc8fdb6462fad27e37eafac8180bfbacf4aa37af2a16c88bb456efe1f017d2","schema_version":"1.0","event_id":"sha256:81cc8fdb6462fad27e37eafac8180bfbacf4aa37af2a16c88bb456efe1f017d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:LCN3AL6DS6VVF2UXHVAA3IZBRV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Jintai Chen, Ling Yue, Sixue Xing, Tianfan Fu","submitted_at":"2024-04-23T06:30:53Z","abstract_excerpt":"Large Language Models (LLMs) and multi-agent systems have shown impressive capabilities in natural language tasks but face challenges in clinical trial applications, primarily due to limited access to external knowledge. Recognizing the potential of advanced clinical trial tools that aggregate and predict based on the latest medical data, we propose an integrated solution to enhance their accessibility and utility. We introduce Clinical Agent System (ClinicalAgent), a clinical multi-agent system designed for clinical trial tasks, leveraging GPT-4, multi-agent architectures, LEAST-TO-MOST, and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.14777","kind":"arxiv","version":2},"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/2404.14777/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":"2026-07-05T08:46:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g0ltNQpQ6ZRlq9N0EwGHsQ4XO/vT1wiwv+hUJR52RcGpVTzVR5rUTxW5UAmEWY8Te385Jwv6y8sXxhnhI3cQDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T07:21:18.848872Z"},"content_sha256":"141e85a65266fb91a024f7cd26049adc18c003828f34476ac655852273f18866","schema_version":"1.0","event_id":"sha256:141e85a65266fb91a024f7cd26049adc18c003828f34476ac655852273f18866"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LCN3AL6DS6VVF2UXHVAA3IZBRV/bundle.json","state_url":"https://pith.science/pith/LCN3AL6DS6VVF2UXHVAA3IZBRV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LCN3AL6DS6VVF2UXHVAA3IZBRV/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":"2026-08-06T07:21:18Z","links":{"resolver":"https://pith.science/pith/LCN3AL6DS6VVF2UXHVAA3IZBRV","bundle":"https://pith.science/pith/LCN3AL6DS6VVF2UXHVAA3IZBRV/bundle.json","state":"https://pith.science/pith/LCN3AL6DS6VVF2UXHVAA3IZBRV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LCN3AL6DS6VVF2UXHVAA3IZBRV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LCN3AL6DS6VVF2UXHVAA3IZBRV","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":"f07dedb1109c79f27acb774896232221bb687707b71ec2d13f5ca0f79693e512","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T06:30:53Z","title_canon_sha256":"9e338a7e9348df7b6707351f1ddce7cec231f37e79eb3523eccf67aed89c796e"},"schema_version":"1.0","source":{"id":"2404.14777","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.14777","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"arxiv_version","alias_value":"2404.14777v2","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.14777","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"pith_short_12","alias_value":"LCN3AL6DS6VV","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"pith_short_16","alias_value":"LCN3AL6DS6VVF2UX","created_at":"2026-07-05T08:46:24Z"},{"alias_kind":"pith_short_8","alias_value":"LCN3AL6D","created_at":"2026-07-05T08:46:24Z"}],"graph_snapshots":[{"event_id":"sha256:141e85a65266fb91a024f7cd26049adc18c003828f34476ac655852273f18866","target":"graph","created_at":"2026-07-05T08:46:24Z","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/2404.14777/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) and multi-agent systems have shown impressive capabilities in natural language tasks but face challenges in clinical trial applications, primarily due to limited access to external knowledge. Recognizing the potential of advanced clinical trial tools that aggregate and predict based on the latest medical data, we propose an integrated solution to enhance their accessibility and utility. We introduce Clinical Agent System (ClinicalAgent), a clinical multi-agent system designed for clinical trial tasks, leveraging GPT-4, multi-agent architectures, LEAST-TO-MOST, and ","authors_text":"Jintai Chen, Ling Yue, Sixue Xing, Tianfan Fu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T06:30:53Z","title":"ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.14777","kind":"arxiv","version":2},"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":"sha256:81cc8fdb6462fad27e37eafac8180bfbacf4aa37af2a16c88bb456efe1f017d2","target":"record","created_at":"2026-07-05T08:46:24Z","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":"f07dedb1109c79f27acb774896232221bb687707b71ec2d13f5ca0f79693e512","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-23T06:30:53Z","title_canon_sha256":"9e338a7e9348df7b6707351f1ddce7cec231f37e79eb3523eccf67aed89c796e"},"schema_version":"1.0","source":{"id":"2404.14777","kind":"arxiv","version":2}},"canonical_sha256":"589bb02fc397ab52ea973d400da3218d7651254ddef83ff50719c43a77f77824","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"589bb02fc397ab52ea973d400da3218d7651254ddef83ff50719c43a77f77824","first_computed_at":"2026-07-05T08:46:24.360312Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:46:24.360312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9YADHWwpIt6fL6rp+Dz7XXfg1zw00C0aBkPfCY6mT51p3ppPqVpbI4HkUnaLJqWXtEpDgguqMOCO0IlJhRZsDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:46:24.360828Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.14777","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:81cc8fdb6462fad27e37eafac8180bfbacf4aa37af2a16c88bb456efe1f017d2","sha256:141e85a65266fb91a024f7cd26049adc18c003828f34476ac655852273f18866"],"state_sha256":"a6d02f2efcc2a47600aec27c09f65db88007af5f5df1e56e37ca9ee63888a339"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M2+8VVWy9u64Q5aRj/9slkzukomZxeMUXUJNCl2kzx8gkXUPnS4IoBxlkb/R8LnGwCP4aTI9lpRpOivx4tnCDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T07:21:18.852686Z","bundle_sha256":"d8d8721c0ecd0f3708b399fb084338aa51f88e644bddcfa001712e65ba0bddbf"}}