{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:CGLCQKAV7D25O7FPZCHNO5Z3NK","short_pith_number":"pith:CGLCQKAV","schema_version":"1.0","canonical_sha256":"1196282815f8f5d77cafc88ed7773b6ab96c104474a25b1ba52650ace9c33a00","source":{"kind":"arxiv","id":"2605.19373","version":1},"attestation_state":"computed","paper":{"title":"Conflict-Free Replicated Data Types for Neural Network Model Merging: A Two-Layer Architecture Enabling CRDT-Compliant Model Merging Across 26 Strategies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.DC","authors_text":"Ryan Gillespie","submitted_at":"2026-05-16T07:08:52Z","abstract_excerpt":"All 26 neural network merge strategies we tested including weight averaging, SLERP, TIES, DARE, Fisher merging, and evolutionary approaches -- fail the algebraic properties (commutativity, associativity, idempotency) required for conflict-free distributed operation. We prove that this failure is structural: normalisation-based merges cannot simultaneously satisfy all three properties. To resolve this, we present a two-layer architecture -- CRDTMergeState -- that wraps any merge strategy in a CRDT-compliant (Conflict-Free Replicated Data Type) layer. Layer 1 manages contributions via OR-Set CRD"},"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":"2605.19373","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2026-05-16T07:08:52Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"251ffd1df4f905d098b998ce26377f19a4a36efc5a61cce38fb02fb9e120d1b3","abstract_canon_sha256":"e8b6af393f1e9e8691ef438cbc7caac6149bc25a152dfa842a775bf2ec10bf92"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:05:42.408734Z","signature_b64":"Hz27k8w+xusNnnXC1ZxBA3CT9UO1w4bSXEdGqEAOxUouRgC1weoKiMLLksEXk/TI2Q66J7QktNI+SNkDuT4mDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1196282815f8f5d77cafc88ed7773b6ab96c104474a25b1ba52650ace9c33a00","last_reissued_at":"2026-05-20T01:05:42.408113Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:05:42.408113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Conflict-Free Replicated Data Types for Neural Network Model Merging: A Two-Layer Architecture Enabling CRDT-Compliant Model Merging Across 26 Strategies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.DC","authors_text":"Ryan Gillespie","submitted_at":"2026-05-16T07:08:52Z","abstract_excerpt":"All 26 neural network merge strategies we tested including weight averaging, SLERP, TIES, DARE, Fisher merging, and evolutionary approaches -- fail the algebraic properties (commutativity, associativity, idempotency) required for conflict-free distributed operation. We prove that this failure is structural: normalisation-based merges cannot simultaneously satisfy all three properties. To resolve this, we present a two-layer architecture -- CRDTMergeState -- that wraps any merge strategy in a CRDT-compliant (Conflict-Free Replicated Data Type) layer. Layer 1 manages contributions via OR-Set CRD"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19373","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/2605.19373/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":"2605.19373","created_at":"2026-05-20T01:05:42.408234+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.19373v1","created_at":"2026-05-20T01:05:42.408234+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19373","created_at":"2026-05-20T01:05:42.408234+00:00"},{"alias_kind":"pith_short_12","alias_value":"CGLCQKAV7D25","created_at":"2026-05-20T01:05:42.408234+00:00"},{"alias_kind":"pith_short_16","alias_value":"CGLCQKAV7D25O7FP","created_at":"2026-05-20T01:05:42.408234+00:00"},{"alias_kind":"pith_short_8","alias_value":"CGLCQKAV","created_at":"2026-05-20T01:05:42.408234+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/CGLCQKAV7D25O7FPZCHNO5Z3NK","json":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK.json","graph_json":"https://pith.science/api/pith-number/CGLCQKAV7D25O7FPZCHNO5Z3NK/graph.json","events_json":"https://pith.science/api/pith-number/CGLCQKAV7D25O7FPZCHNO5Z3NK/events.json","paper":"https://pith.science/paper/CGLCQKAV"},"agent_actions":{"view_html":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK","download_json":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK.json","view_paper":"https://pith.science/paper/CGLCQKAV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.19373&json=true","fetch_graph":"https://pith.science/api/pith-number/CGLCQKAV7D25O7FPZCHNO5Z3NK/graph.json","fetch_events":"https://pith.science/api/pith-number/CGLCQKAV7D25O7FPZCHNO5Z3NK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK/action/storage_attestation","attest_author":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK/action/author_attestation","sign_citation":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK/action/citation_signature","submit_replication":"https://pith.science/pith/CGLCQKAV7D25O7FPZCHNO5Z3NK/action/replication_record"}},"created_at":"2026-05-20T01:05:42.408234+00:00","updated_at":"2026-05-20T01:05:42.408234+00:00"}