{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:FB2SCDBETHJBRWIQKSCRKOTRTE","short_pith_number":"pith:FB2SCDBE","canonical_record":{"source":{"id":"2605.29744","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T10:42:44Z","cross_cats_sorted":["cs.CL","cs.LG","cs.MA"],"title_canon_sha256":"0550078034f0b2ede330e87ad6b37810eb15266e78013a850bd856768800413a","abstract_canon_sha256":"f2e3cbc57607f4bb75f39f7382186cd4e6cbcec85aa552f3456a50ac34bf007c"},"schema_version":"1.0"},"canonical_sha256":"2875210c2499d218d9105485153a71993b66f6565885cd9d5e1a9742fbf86742","source":{"kind":"arxiv","id":"2605.29744","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.29744","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"arxiv_version","alias_value":"2605.29744v1","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29744","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"pith_short_12","alias_value":"FB2SCDBETHJB","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"pith_short_16","alias_value":"FB2SCDBETHJBRWIQ","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"pith_short_8","alias_value":"FB2SCDBE","created_at":"2026-05-29T01:05:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:FB2SCDBETHJBRWIQKSCRKOTRTE","target":"record","payload":{"canonical_record":{"source":{"id":"2605.29744","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T10:42:44Z","cross_cats_sorted":["cs.CL","cs.LG","cs.MA"],"title_canon_sha256":"0550078034f0b2ede330e87ad6b37810eb15266e78013a850bd856768800413a","abstract_canon_sha256":"f2e3cbc57607f4bb75f39f7382186cd4e6cbcec85aa552f3456a50ac34bf007c"},"schema_version":"1.0"},"canonical_sha256":"2875210c2499d218d9105485153a71993b66f6565885cd9d5e1a9742fbf86742","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T01:05:57.646741Z","signature_b64":"ZBluISqTZ0fz+TPnL265jkt0IZryg8CNP/2aCrAa72iHwx0hkBhCrU+06X3xRmuYqri+bmYjt+dOx1XC9r5ZAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2875210c2499d218d9105485153a71993b66f6565885cd9d5e1a9742fbf86742","last_reissued_at":"2026-05-29T01:05:57.646249Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T01:05:57.646249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.29744","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":"2026-05-29T01:05:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kZKSA/VMyVp/qolRjtyvJUjESRkHIPYVhz4XB+P6zth+LaURR7BisdHw2HQnQCrJtuPmETxsb50ZLtuHhBDYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T15:20:50.679021Z"},"content_sha256":"bcc54cc818655aff6e070f6716506f0a89cfbceec07e59aa8517eb82fc3f7574","schema_version":"1.0","event_id":"sha256:bcc54cc818655aff6e070f6716506f0a89cfbceec07e59aa8517eb82fc3f7574"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:FB2SCDBETHJBRWIQKSCRKOTRTE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Why Specialist Models Still Matter: A Heterogeneous Multi-Agent Paradigm for Medical Artificial Intelligence","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.MA"],"primary_cat":"cs.AI","authors_text":"Aiguo Wang, Cuiwei Yang, Guohui Zhou, Jian Liu, Shuaicong Hu, Yanan Wang","submitted_at":"2026-05-28T10:42:44Z","abstract_excerpt":"The impressive performance of generalist large language models (LLMs) such as GPT and Claude in healthcare raises a critical question: will domain-specific medical specialist models become obsolete? We argue that the future of medical artificial intelligence (AI) lies not in building monolithic medical foundation models, nor in replacing human expertise, but in orchestrating collaboration among generalist LLMs, domain-specific specialist models, and clinicians. We propose HetMedAgent, a heterogeneous medical multi-agent framework that enables conflict-aware evidence fusion, uncertainty-based c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29744","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/2605.29744/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":"2026-05-29T01:05:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oSU9XbkMJ6x1P+3a2ZtQ9j/sd+z0c+g+g3Vjlt3EVdmcXfdP5+aGgmaeadakR+WVaHZPC4jdV6zY+ZphdSlDCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T15:20:50.679413Z"},"content_sha256":"25fe2a436902c4e31aacbb64a7d1dfeea19a2c14dcd910ecf16678cb77c2de44","schema_version":"1.0","event_id":"sha256:25fe2a436902c4e31aacbb64a7d1dfeea19a2c14dcd910ecf16678cb77c2de44"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FB2SCDBETHJBRWIQKSCRKOTRTE/bundle.json","state_url":"https://pith.science/pith/FB2SCDBETHJBRWIQKSCRKOTRTE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FB2SCDBETHJBRWIQKSCRKOTRTE/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":"2026-06-29T15:20:50Z","links":{"resolver":"https://pith.science/pith/FB2SCDBETHJBRWIQKSCRKOTRTE","bundle":"https://pith.science/pith/FB2SCDBETHJBRWIQKSCRKOTRTE/bundle.json","state":"https://pith.science/pith/FB2SCDBETHJBRWIQKSCRKOTRTE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FB2SCDBETHJBRWIQKSCRKOTRTE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:FB2SCDBETHJBRWIQKSCRKOTRTE","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":"f2e3cbc57607f4bb75f39f7382186cd4e6cbcec85aa552f3456a50ac34bf007c","cross_cats_sorted":["cs.CL","cs.LG","cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T10:42:44Z","title_canon_sha256":"0550078034f0b2ede330e87ad6b37810eb15266e78013a850bd856768800413a"},"schema_version":"1.0","source":{"id":"2605.29744","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.29744","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"arxiv_version","alias_value":"2605.29744v1","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29744","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"pith_short_12","alias_value":"FB2SCDBETHJB","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"pith_short_16","alias_value":"FB2SCDBETHJBRWIQ","created_at":"2026-05-29T01:05:57Z"},{"alias_kind":"pith_short_8","alias_value":"FB2SCDBE","created_at":"2026-05-29T01:05:57Z"}],"graph_snapshots":[{"event_id":"sha256:25fe2a436902c4e31aacbb64a7d1dfeea19a2c14dcd910ecf16678cb77c2de44","target":"graph","created_at":"2026-05-29T01:05:57Z","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/2605.29744/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The impressive performance of generalist large language models (LLMs) such as GPT and Claude in healthcare raises a critical question: will domain-specific medical specialist models become obsolete? We argue that the future of medical artificial intelligence (AI) lies not in building monolithic medical foundation models, nor in replacing human expertise, but in orchestrating collaboration among generalist LLMs, domain-specific specialist models, and clinicians. We propose HetMedAgent, a heterogeneous medical multi-agent framework that enables conflict-aware evidence fusion, uncertainty-based c","authors_text":"Aiguo Wang, Cuiwei Yang, Guohui Zhou, Jian Liu, Shuaicong Hu, Yanan Wang","cross_cats":["cs.CL","cs.LG","cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T10:42:44Z","title":"Why Specialist Models Still Matter: A Heterogeneous Multi-Agent Paradigm for Medical Artificial Intelligence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29744","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:bcc54cc818655aff6e070f6716506f0a89cfbceec07e59aa8517eb82fc3f7574","target":"record","created_at":"2026-05-29T01:05:57Z","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":"f2e3cbc57607f4bb75f39f7382186cd4e6cbcec85aa552f3456a50ac34bf007c","cross_cats_sorted":["cs.CL","cs.LG","cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T10:42:44Z","title_canon_sha256":"0550078034f0b2ede330e87ad6b37810eb15266e78013a850bd856768800413a"},"schema_version":"1.0","source":{"id":"2605.29744","kind":"arxiv","version":1}},"canonical_sha256":"2875210c2499d218d9105485153a71993b66f6565885cd9d5e1a9742fbf86742","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2875210c2499d218d9105485153a71993b66f6565885cd9d5e1a9742fbf86742","first_computed_at":"2026-05-29T01:05:57.646249Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T01:05:57.646249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZBluISqTZ0fz+TPnL265jkt0IZryg8CNP/2aCrAa72iHwx0hkBhCrU+06X3xRmuYqri+bmYjt+dOx1XC9r5ZAw==","signature_status":"signed_v1","signed_at":"2026-05-29T01:05:57.646741Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.29744","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bcc54cc818655aff6e070f6716506f0a89cfbceec07e59aa8517eb82fc3f7574","sha256:25fe2a436902c4e31aacbb64a7d1dfeea19a2c14dcd910ecf16678cb77c2de44"],"state_sha256":"b0bdd258a872ad5541b8e05951591ae38033d61d2cc569f5fe24b64e014df0d1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LSwAmFjsd2n+CaySBCwHanF1p0/Ub5zsGSRuMiY3KWD1hY3aRwy02HwjrgpySQ9ypAgCZDZGBrsM3S/htQybDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T15:20:50.681416Z","bundle_sha256":"c632d1b734d8c7469d85f49da0628c11dc80ff43e6752c38e230a490a772fb41"}}