{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LDRNUKSMIRZB7XOEFYR4Z6ZQSX","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":"44988efb9a08282d0985fee87cb8195fe9e59c899df41b09c5b16c26cfb5cb1e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-07-13T13:58:24Z","title_canon_sha256":"8a2062d916b1764ea34c18b5f3bc0a710a60afeb1ec717013ae86e7a5f3a7501"},"schema_version":"1.0","source":{"id":"2407.09893","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.09893","created_at":"2026-07-05T09:55:58Z"},{"alias_kind":"arxiv_version","alias_value":"2407.09893v3","created_at":"2026-07-05T09:55:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.09893","created_at":"2026-07-05T09:55:58Z"},{"alias_kind":"pith_short_12","alias_value":"LDRNUKSMIRZB","created_at":"2026-07-05T09:55:58Z"},{"alias_kind":"pith_short_16","alias_value":"LDRNUKSMIRZB7XOE","created_at":"2026-07-05T09:55:58Z"},{"alias_kind":"pith_short_8","alias_value":"LDRNUKSM","created_at":"2026-07-05T09:55:58Z"}],"graph_snapshots":[{"event_id":"sha256:8db912ce38c36a33de5204f9897b94f593a634427e2da100d8b6ea745c4f7c11","target":"graph","created_at":"2026-07-05T09:55:58Z","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/2407.09893/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in Large Language Models (LLMs) have led to significant breakthroughs in various natural language processing tasks. However, generating factually consistent responses in knowledge-intensive scenarios remains a challenge due to issues such as hallucination, difficulty in acquiring long-tailed knowledge, and limited memory expansion. This paper introduces SMART, a novel multi-agent framework that leverages external knowledge to enhance the interpretability and factual consistency of LLM-generated responses. SMART comprises four specialized agents, each performing a specific s","authors_text":"Shengbin Yue, Siyuan Wang, Wei Chen, Xuanjing Huang, Zhongyu Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-07-13T13:58:24Z","title":"Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.09893","kind":"arxiv","version":3},"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":"sha256:9871070cf5111ee8749bf5865fefc2a86cd7c491b18e81fbbd137fac3dc562a5","target":"record","created_at":"2026-07-05T09:55:58Z","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":"44988efb9a08282d0985fee87cb8195fe9e59c899df41b09c5b16c26cfb5cb1e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-07-13T13:58:24Z","title_canon_sha256":"8a2062d916b1764ea34c18b5f3bc0a710a60afeb1ec717013ae86e7a5f3a7501"},"schema_version":"1.0","source":{"id":"2407.09893","kind":"arxiv","version":3}},"canonical_sha256":"58e2da2a4c44721fddc42e23ccfb3095e0bcaea292edaf44fdc11108aec5d818","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"58e2da2a4c44721fddc42e23ccfb3095e0bcaea292edaf44fdc11108aec5d818","first_computed_at":"2026-07-05T09:55:58.584715Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:55:58.584715Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CCZW/l1pYrGrye8BtykTE73RdCW0jC1X+AF6Lup4ZaRp6fMbLVZ57vLAbDyFekhtaO5um06P7X8XFomNNuKHAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:55:58.585124Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.09893","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9871070cf5111ee8749bf5865fefc2a86cd7c491b18e81fbbd137fac3dc562a5","sha256:8db912ce38c36a33de5204f9897b94f593a634427e2da100d8b6ea745c4f7c11"],"state_sha256":"924c528435950cf8e8b420c7fce57d4a728af92e848c15f4f9c6d813174b0bed"}