{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OATQA2ZT2LRIWCAY5XQELGY5GM","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":"7b127392cde1a1a5c0587ee52144e1872dffa3fdd5ce3535f866273f731a1681","cross_cats_sorted":["cs.AI","cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-13T20:43:46Z","title_canon_sha256":"ca6975ba6f1afe97bad32c552b79e57d113486bc9e20acf301aeec944fe716c4"},"schema_version":"1.0","source":{"id":"2404.09077","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.09077","created_at":"2026-07-05T10:15:43Z"},{"alias_kind":"arxiv_version","alias_value":"2404.09077v3","created_at":"2026-07-05T10:15:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.09077","created_at":"2026-07-05T10:15:43Z"},{"alias_kind":"pith_short_12","alias_value":"OATQA2ZT2LRI","created_at":"2026-07-05T10:15:43Z"},{"alias_kind":"pith_short_16","alias_value":"OATQA2ZT2LRIWCAY","created_at":"2026-07-05T10:15:43Z"},{"alias_kind":"pith_short_8","alias_value":"OATQA2ZT","created_at":"2026-07-05T10:15:43Z"}],"graph_snapshots":[{"event_id":"sha256:f786dfc1bf9835298b88583c63747180bd6765f6d2d70c429add2b6a38d6f0e7","target":"graph","created_at":"2026-07-05T10:15:43Z","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/2404.09077/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have achieved significant success in open-domain question answering. However, they continue to face challenges such as hallucinations and knowledge cutoffs. These issues can be mitigated through in-context learning by providing LLMs with relevant context before generating answers. Recent literature proposes Knowledge Graph Prompting (KGP) which integrates knowledge graphs with an LLM-based traversal agent to substantially enhance document retrieval quality. However, KGP requires costly fine-tuning with large datasets and remains prone to hallucination. In this pape","authors_text":"Xuan Zhu, Zixuan Zhu, Zukang Yang","cross_cats":["cs.AI","cs.IR","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-13T20:43:46Z","title":"CuriousLLM: Elevating Multi-Document Question Answering with LLM-Enhanced Knowledge Graph Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.09077","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:e59a369719ab0712537ab9617e3a55c5475d38a395b952902b444f99d2a7fad6","target":"record","created_at":"2026-07-05T10:15:43Z","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":"7b127392cde1a1a5c0587ee52144e1872dffa3fdd5ce3535f866273f731a1681","cross_cats_sorted":["cs.AI","cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-13T20:43:46Z","title_canon_sha256":"ca6975ba6f1afe97bad32c552b79e57d113486bc9e20acf301aeec944fe716c4"},"schema_version":"1.0","source":{"id":"2404.09077","kind":"arxiv","version":3}},"canonical_sha256":"7027006b33d2e28b0818ede0459b1d332317daa6e3933a5a048fbd04cfa3d05e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7027006b33d2e28b0818ede0459b1d332317daa6e3933a5a048fbd04cfa3d05e","first_computed_at":"2026-07-05T10:15:43.459939Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:15:43.459939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6Quv2cSLUb1acJdJzl9qWrxxDehnk06R8q+NbQQN3VGdkjVR1wOS/6Q3kKRBEoHhxZXeuzynzW38ER9TkvFaBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:15:43.460556Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.09077","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e59a369719ab0712537ab9617e3a55c5475d38a395b952902b444f99d2a7fad6","sha256:f786dfc1bf9835298b88583c63747180bd6765f6d2d70c429add2b6a38d6f0e7"],"state_sha256":"2596b674b6ec2d81298108705537caff1c1e0f4955b4f4e3c65102288c3e9058"}