{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:DCJVUYXLAAOYHWLCTLNE7FHMIU","short_pith_number":"pith:DCJVUYXL","canonical_record":{"source":{"id":"2508.13754","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-08-19T11:51:15Z","cross_cats_sorted":[],"title_canon_sha256":"2d80e89bd38c9e494ea094ea00fc260c7371bea22eef91688abfbdd31597a306","abstract_canon_sha256":"ac9e57271e85dbd3296a66c06e0971a00f41d9733715e51e013b8364c04727be"},"schema_version":"1.0"},"canonical_sha256":"18935a62eb001d83d9629ada4f94ec4507d7da5e4f1d90184e86b5bcbdc64ace","source":{"kind":"arxiv","id":"2508.13754","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.13754","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"arxiv_version","alias_value":"2508.13754v1","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.13754","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"pith_short_12","alias_value":"DCJVUYXLAAOY","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"pith_short_16","alias_value":"DCJVUYXLAAOYHWLC","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"pith_short_8","alias_value":"DCJVUYXL","created_at":"2026-07-05T11:56:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:DCJVUYXLAAOYHWLCTLNE7FHMIU","target":"record","payload":{"canonical_record":{"source":{"id":"2508.13754","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-08-19T11:51:15Z","cross_cats_sorted":[],"title_canon_sha256":"2d80e89bd38c9e494ea094ea00fc260c7371bea22eef91688abfbdd31597a306","abstract_canon_sha256":"ac9e57271e85dbd3296a66c06e0971a00f41d9733715e51e013b8364c04727be"},"schema_version":"1.0"},"canonical_sha256":"18935a62eb001d83d9629ada4f94ec4507d7da5e4f1d90184e86b5bcbdc64ace","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:56:07.150552Z","signature_b64":"PVU4lydUvK+f5uUMWSYVq+fXlQVfqR4pJafEVJFvp/Q6V6VqUnNotf0dB8dyXj4MHZKOrZ1bNSl/xufDPDnwCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"18935a62eb001d83d9629ada4f94ec4507d7da5e4f1d90184e86b5bcbdc64ace","last_reissued_at":"2026-07-05T11:56:07.150120Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:56:07.150120Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.13754","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:56:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qm0U2liWJJ4AqGovjp/eOzNwgYRRciuPoxhfjD17euwH0HooR0CU/ppeperiy+2jywcsQsTfRow7rY5SJWpiDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T18:21:39.739884Z"},"content_sha256":"bb1210b5c6e4bdc8ac6f148ec419cf657908f635a21fd2d0ac5564d6078b2212","schema_version":"1.0","event_id":"sha256:bb1210b5c6e4bdc8ac6f148ec419cf657908f635a21fd2d0ac5564d6078b2212"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:DCJVUYXLAAOYHWLCTLNE7FHMIU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Making","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jiyong Zhang, Liuxin Bao, Runmin Cong, Xiaofei Zhou, Yixuan Yuan, Zhihao Peng","submitted_at":"2025-08-19T11:51:15Z","abstract_excerpt":"Medical Decision-Making (MDM) is a complex process requiring substantial domain-specific expertise to effectively synthesize heterogeneous and complicated clinical information. While recent advancements in Large Language Models (LLMs) show promise in supporting MDM, single-LLM approaches are limited by their parametric knowledge constraints and static training corpora, failing to robustly integrate the clinical information. To address this challenge, we propose the Expertise-aware Multi-LLM Recruitment and Collaboration (EMRC) framework to enhance the accuracy and reliability of MDM systems. I"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.13754","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/2508.13754/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":"2026-07-05T11:56:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nW8tYIJk8F8KQ1SD1oEsf2xrHUHVqAjVo+TXlm3IEUbDdxDA/KFIL7wv7KaDFk50YYAErL1cHouLWz3JRNt4Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T18:21:39.743383Z"},"content_sha256":"b29790949e3f2106790a4ec5d4354c2fdb3267ffc50c2551dab2ecc15acaf29e","schema_version":"1.0","event_id":"sha256:b29790949e3f2106790a4ec5d4354c2fdb3267ffc50c2551dab2ecc15acaf29e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DCJVUYXLAAOYHWLCTLNE7FHMIU/bundle.json","state_url":"https://pith.science/pith/DCJVUYXLAAOYHWLCTLNE7FHMIU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DCJVUYXLAAOYHWLCTLNE7FHMIU/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":"2026-08-12T18:21:39Z","links":{"resolver":"https://pith.science/pith/DCJVUYXLAAOYHWLCTLNE7FHMIU","bundle":"https://pith.science/pith/DCJVUYXLAAOYHWLCTLNE7FHMIU/bundle.json","state":"https://pith.science/pith/DCJVUYXLAAOYHWLCTLNE7FHMIU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DCJVUYXLAAOYHWLCTLNE7FHMIU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DCJVUYXLAAOYHWLCTLNE7FHMIU","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":"ac9e57271e85dbd3296a66c06e0971a00f41d9733715e51e013b8364c04727be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-08-19T11:51:15Z","title_canon_sha256":"2d80e89bd38c9e494ea094ea00fc260c7371bea22eef91688abfbdd31597a306"},"schema_version":"1.0","source":{"id":"2508.13754","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.13754","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"arxiv_version","alias_value":"2508.13754v1","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.13754","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"pith_short_12","alias_value":"DCJVUYXLAAOY","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"pith_short_16","alias_value":"DCJVUYXLAAOYHWLC","created_at":"2026-07-05T11:56:07Z"},{"alias_kind":"pith_short_8","alias_value":"DCJVUYXL","created_at":"2026-07-05T11:56:07Z"}],"graph_snapshots":[{"event_id":"sha256:b29790949e3f2106790a4ec5d4354c2fdb3267ffc50c2551dab2ecc15acaf29e","target":"graph","created_at":"2026-07-05T11:56:07Z","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/2508.13754/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Medical Decision-Making (MDM) is a complex process requiring substantial domain-specific expertise to effectively synthesize heterogeneous and complicated clinical information. While recent advancements in Large Language Models (LLMs) show promise in supporting MDM, single-LLM approaches are limited by their parametric knowledge constraints and static training corpora, failing to robustly integrate the clinical information. To address this challenge, we propose the Expertise-aware Multi-LLM Recruitment and Collaboration (EMRC) framework to enhance the accuracy and reliability of MDM systems. I","authors_text":"Jiyong Zhang, Liuxin Bao, Runmin Cong, Xiaofei Zhou, Yixuan Yuan, Zhihao Peng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-08-19T11:51:15Z","title":"Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Making"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.13754","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:bb1210b5c6e4bdc8ac6f148ec419cf657908f635a21fd2d0ac5564d6078b2212","target":"record","created_at":"2026-07-05T11:56:07Z","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":"ac9e57271e85dbd3296a66c06e0971a00f41d9733715e51e013b8364c04727be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-08-19T11:51:15Z","title_canon_sha256":"2d80e89bd38c9e494ea094ea00fc260c7371bea22eef91688abfbdd31597a306"},"schema_version":"1.0","source":{"id":"2508.13754","kind":"arxiv","version":1}},"canonical_sha256":"18935a62eb001d83d9629ada4f94ec4507d7da5e4f1d90184e86b5bcbdc64ace","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"18935a62eb001d83d9629ada4f94ec4507d7da5e4f1d90184e86b5bcbdc64ace","first_computed_at":"2026-07-05T11:56:07.150120Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:56:07.150120Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PVU4lydUvK+f5uUMWSYVq+fXlQVfqR4pJafEVJFvp/Q6V6VqUnNotf0dB8dyXj4MHZKOrZ1bNSl/xufDPDnwCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:56:07.150552Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.13754","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb1210b5c6e4bdc8ac6f148ec419cf657908f635a21fd2d0ac5564d6078b2212","sha256:b29790949e3f2106790a4ec5d4354c2fdb3267ffc50c2551dab2ecc15acaf29e"],"state_sha256":"001de5f54a2aa4a23e15102ac9f68948077ae9c8fd04348949024fced799a06c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5XSFltwx5RXimiNz6uu+wFJQA5C4a23jYB4+bfO2tEP12nDqfIQSR4+A645pwmRbanb2yhKkLE1ZEfszeBjcCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T18:21:39.756194Z","bundle_sha256":"5dc0c5148fa41f29e51fd51e6ef469a718cfc551ba9b3c75f22617cc0b7ac92c"}}