{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:LI45W7UGCL4SACZ22GEACIZ26X","short_pith_number":"pith:LI45W7UG","schema_version":"1.0","canonical_sha256":"5a39db7e8612f9200b3ad18801233af5c2467d52cd6dcee26ca1d98a1a0f317b","source":{"kind":"arxiv","id":"2510.05746","version":2},"attestation_state":"computed","paper":{"title":"ARM: Discovering Agentic Reasoning Modules for Generalizable Multi-Agent Systems","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.AI","authors_text":"Bohan Yao, Shiva Krishna Reddy Malay, Vikas Yadav","submitted_at":"2025-10-07T10:04:48Z","abstract_excerpt":"Large Language Model (LLM)-powered Multi-agent systems (MAS) have achieved state-of-the-art results on various complex reasoning tasks. Recent works have proposed techniques to automate the design of MASes, eliminating the need for manual engineering. However, these techniques perform poorly, often achieving similar or inferior performance to simple baselines. Furthermore, they require computationally expensive re-discovery of architectures for each new task domain and expensive data annotation on domains without existing labeled validation sets. A critical insight is that simple Chain of Thou"},"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":"2510.05746","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-10-07T10:04:48Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"6d7d57590a10771e6df075953e6fc11272ffc1151ad9917ebd5d9c4b76b23785","abstract_canon_sha256":"d7f6901993bfc8dfbae887170f1ab97ddcf2c5d0bc30a7ff257aa93c28d41014"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:04:59.542348Z","signature_b64":"PIbxuX1eUtr9F23xxdP67oQIrSoQjHWQ8x0tLafax+0hDhZ5e7IjatL3vKJnuBLaZS8eNEaEQX6Y2hAqq3YOAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5a39db7e8612f9200b3ad18801233af5c2467d52cd6dcee26ca1d98a1a0f317b","last_reissued_at":"2026-05-20T01:04:59.541174Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:04:59.541174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ARM: Discovering Agentic Reasoning Modules for Generalizable Multi-Agent Systems","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.AI","authors_text":"Bohan Yao, Shiva Krishna Reddy Malay, Vikas Yadav","submitted_at":"2025-10-07T10:04:48Z","abstract_excerpt":"Large Language Model (LLM)-powered Multi-agent systems (MAS) have achieved state-of-the-art results on various complex reasoning tasks. Recent works have proposed techniques to automate the design of MASes, eliminating the need for manual engineering. However, these techniques perform poorly, often achieving similar or inferior performance to simple baselines. Furthermore, they require computationally expensive re-discovery of architectures for each new task domain and expensive data annotation on domains without existing labeled validation sets. A critical insight is that simple Chain of Thou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.05746","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/2510.05746/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":"2510.05746","created_at":"2026-05-20T01:04:59.541338+00:00"},{"alias_kind":"arxiv_version","alias_value":"2510.05746v2","created_at":"2026-05-20T01:04:59.541338+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.05746","created_at":"2026-05-20T01:04:59.541338+00:00"},{"alias_kind":"pith_short_12","alias_value":"LI45W7UGCL4S","created_at":"2026-05-20T01:04:59.541338+00:00"},{"alias_kind":"pith_short_16","alias_value":"LI45W7UGCL4SACZ2","created_at":"2026-05-20T01:04:59.541338+00:00"},{"alias_kind":"pith_short_8","alias_value":"LI45W7UG","created_at":"2026-05-20T01:04:59.541338+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/LI45W7UGCL4SACZ22GEACIZ26X","json":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X.json","graph_json":"https://pith.science/api/pith-number/LI45W7UGCL4SACZ22GEACIZ26X/graph.json","events_json":"https://pith.science/api/pith-number/LI45W7UGCL4SACZ22GEACIZ26X/events.json","paper":"https://pith.science/paper/LI45W7UG"},"agent_actions":{"view_html":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X","download_json":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X.json","view_paper":"https://pith.science/paper/LI45W7UG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2510.05746&json=true","fetch_graph":"https://pith.science/api/pith-number/LI45W7UGCL4SACZ22GEACIZ26X/graph.json","fetch_events":"https://pith.science/api/pith-number/LI45W7UGCL4SACZ22GEACIZ26X/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X/action/storage_attestation","attest_author":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X/action/author_attestation","sign_citation":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X/action/citation_signature","submit_replication":"https://pith.science/pith/LI45W7UGCL4SACZ22GEACIZ26X/action/replication_record"}},"created_at":"2026-05-20T01:04:59.541338+00:00","updated_at":"2026-05-20T01:04:59.541338+00:00"}