{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:B5CV3WT5QJSE34RLSI7XO265YC","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":"2fb80bdd2148028f6f5b8606cbf564b0ccb81d694eed1391503949eb7c3e4656","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-27T08:56:57Z","title_canon_sha256":"69e2647f2dcc8d2c8b607d67c0fa45f4f7c3e1ae6ab42197fb1c9da08370f3cf"},"schema_version":"1.0","source":{"id":"2605.28175","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.28175","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"arxiv_version","alias_value":"2605.28175v1","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28175","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_12","alias_value":"B5CV3WT5QJSE","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_16","alias_value":"B5CV3WT5QJSE34RL","created_at":"2026-05-28T01:05:01Z"},{"alias_kind":"pith_short_8","alias_value":"B5CV3WT5","created_at":"2026-05-28T01:05:01Z"}],"graph_snapshots":[{"event_id":"sha256:5d1ac4707bb89912505637f351621275ca01952d2454a2bd1e190b0cbcbd779c","target":"graph","created_at":"2026-05-28T01:05:01Z","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/2605.28175/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have recently been adopted for recommendations due to their ability to understand user intent and item semantics. However, LLM-based recommender systems often rely on parametric knowledge and suffer from outdated knowledge, motivating knowledge graph retrieval-augmented generation (KG-RAG) to ground recommendations on structured, up-to-date KGs. Despite this promise, effective KG-RAG in recommendations faces great challenges. First, users' queries vary in complexity and require KG knowledge at different granularities, whereas existing methods adopt a one-size-fits-","authors_text":"Chengyi Liu, See-kiong Ng, Shanru Lin, Shijie Wang, Wenqi Fan, Xu Xin, Yujuan Ding","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-27T08:56:57Z","title":"Mixture-of-Experts Knowledge Graph Retrieval-Augmented Generation for Multi-Agent LLM-based Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28175","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:ca94ec579e9176882db8b592bef5a5ecc60ac98d2a35cbe577c773417ca2f40f","target":"record","created_at":"2026-05-28T01:05:01Z","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":"2fb80bdd2148028f6f5b8606cbf564b0ccb81d694eed1391503949eb7c3e4656","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-27T08:56:57Z","title_canon_sha256":"69e2647f2dcc8d2c8b607d67c0fa45f4f7c3e1ae6ab42197fb1c9da08370f3cf"},"schema_version":"1.0","source":{"id":"2605.28175","kind":"arxiv","version":1}},"canonical_sha256":"0f455dda7d82644df22b923f776bddc087d9c313942247550175f67f5a5ecbb7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0f455dda7d82644df22b923f776bddc087d9c313942247550175f67f5a5ecbb7","first_computed_at":"2026-05-28T01:05:01.287928Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-28T01:05:01.287928Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZeVjtgY7Olk94/5DxG1RrkHEbTfYEPuW5byiY1a3wAjzxV14topypDgm/ErNJM98eFpZyvMcmBFCv+GvOkfFDA==","signature_status":"signed_v1","signed_at":"2026-05-28T01:05:01.288348Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.28175","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ca94ec579e9176882db8b592bef5a5ecc60ac98d2a35cbe577c773417ca2f40f","sha256:5d1ac4707bb89912505637f351621275ca01952d2454a2bd1e190b0cbcbd779c"],"state_sha256":"25ab655dddcc908ebc28daefd43fb5dba6f13e8889a40285051f4266be4afcb7"}