{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:62MPGOF4TPK56NJX62QPHF5W3S","short_pith_number":"pith:62MPGOF4","schema_version":"1.0","canonical_sha256":"f698f338bc9bd5df3537f6a0f397b6dcab46a0efd68c7e466b3b2318ac1b0fd1","source":{"kind":"arxiv","id":"2606.13197","version":1},"attestation_state":"computed","paper":{"title":"ARMOR-MAD: Adaptive Routing for Heterogeneous Multi-Agent Debate in Large Language Model Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bowen Zhang, Fuqiang Niu","submitted_at":"2026-06-11T11:02:19Z","abstract_excerpt":"Multi-agent debate (MAD) can improve large language model reasoning, but fixed debate pipelines often waste computation and can amplify correlated errors among similar agents. We propose ARMOR-MAD, a training-free heterogeneous MAD framework that treats debate as conditional computation. ARMOR-MAD combines three components: Pre-debate Agreement Routing (PAR) decides whether independently generated Round-0 answers require debate; Early Agreement Stopping Evaluator (EASE) stops debate after convergence; and Semantic Outlier Detection (SOD) down-weights abnormal final answers during aggregation. "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.13197","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-11T11:02:19Z","cross_cats_sorted":[],"title_canon_sha256":"838441a0d17c7e8852682bc0a97cda5d826172f404ad2078245363c0fe0d7289","abstract_canon_sha256":"b29c8251c30c16cc1b321a65e7a300a2bc11236f225300d6561decccd7ed48d2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-12T01:09:46.338340Z","signature_b64":"b8do8AkAabTHnVP9JrVciHAvKN0GW+Bg6vYUgGyC7LNe0bEXyd//EKHfbmL/i6A+9wqzEI7mkPTjZM3jgZpjBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f698f338bc9bd5df3537f6a0f397b6dcab46a0efd68c7e466b3b2318ac1b0fd1","last_reissued_at":"2026-06-12T01:09:46.337481Z","signature_status":"signed_v1","first_computed_at":"2026-06-12T01:09:46.337481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ARMOR-MAD: Adaptive Routing for Heterogeneous Multi-Agent Debate in Large Language Model Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bowen Zhang, Fuqiang Niu","submitted_at":"2026-06-11T11:02:19Z","abstract_excerpt":"Multi-agent debate (MAD) can improve large language model reasoning, but fixed debate pipelines often waste computation and can amplify correlated errors among similar agents. We propose ARMOR-MAD, a training-free heterogeneous MAD framework that treats debate as conditional computation. ARMOR-MAD combines three components: Pre-debate Agreement Routing (PAR) decides whether independently generated Round-0 answers require debate; Early Agreement Stopping Evaluator (EASE) stops debate after convergence; and Semantic Outlier Detection (SOD) down-weights abnormal final answers during aggregation. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.13197","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/2606.13197/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.13197","created_at":"2026-06-12T01:09:46.337632+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.13197v1","created_at":"2026-06-12T01:09:46.337632+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.13197","created_at":"2026-06-12T01:09:46.337632+00:00"},{"alias_kind":"pith_short_12","alias_value":"62MPGOF4TPK5","created_at":"2026-06-12T01:09:46.337632+00:00"},{"alias_kind":"pith_short_16","alias_value":"62MPGOF4TPK56NJX","created_at":"2026-06-12T01:09:46.337632+00:00"},{"alias_kind":"pith_short_8","alias_value":"62MPGOF4","created_at":"2026-06-12T01:09:46.337632+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S","json":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S.json","graph_json":"https://pith.science/api/pith-number/62MPGOF4TPK56NJX62QPHF5W3S/graph.json","events_json":"https://pith.science/api/pith-number/62MPGOF4TPK56NJX62QPHF5W3S/events.json","paper":"https://pith.science/paper/62MPGOF4"},"agent_actions":{"view_html":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S","download_json":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S.json","view_paper":"https://pith.science/paper/62MPGOF4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.13197&json=true","fetch_graph":"https://pith.science/api/pith-number/62MPGOF4TPK56NJX62QPHF5W3S/graph.json","fetch_events":"https://pith.science/api/pith-number/62MPGOF4TPK56NJX62QPHF5W3S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S/action/storage_attestation","attest_author":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S/action/author_attestation","sign_citation":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S/action/citation_signature","submit_replication":"https://pith.science/pith/62MPGOF4TPK56NJX62QPHF5W3S/action/replication_record"}},"created_at":"2026-06-12T01:09:46.337632+00:00","updated_at":"2026-06-12T01:09:46.337632+00:00"}