{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:D7LZOV2SORU32ESFCLQCF6YJJ4","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":"cd620357d44a882d0bd3cee5e114b06b5e092895ee078302ca96bdbc0d7b404c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-02T10:14:43Z","title_canon_sha256":"a0e5c39018e599eef7e04ff9bd704890270becd0863c47bba286f4f9b16df26b"},"schema_version":"1.0","source":{"id":"2310.01061","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.01061","created_at":"2026-07-05T07:48:48Z"},{"alias_kind":"arxiv_version","alias_value":"2310.01061v2","created_at":"2026-07-05T07:48:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.01061","created_at":"2026-07-05T07:48:48Z"},{"alias_kind":"pith_short_12","alias_value":"D7LZOV2SORU3","created_at":"2026-07-05T07:48:48Z"},{"alias_kind":"pith_short_16","alias_value":"D7LZOV2SORU32ESF","created_at":"2026-07-05T07:48:48Z"},{"alias_kind":"pith_short_8","alias_value":"D7LZOV2S","created_at":"2026-07-05T07:48:48Z"}],"graph_snapshots":[{"event_id":"sha256:0432283152e0e26b493b7896a5f19d7e255b7ca0febac5e53ae3a59af10a3050","target":"graph","created_at":"2026-07-05T07:48:48Z","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/2310.01061/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have demonstrated impressive reasoning abilities in complex tasks. However, they lack up-to-date knowledge and experience hallucinations during reasoning, which can lead to incorrect reasoning processes and diminish their performance and trustworthiness. Knowledge graphs (KGs), which capture vast amounts of facts in a structured format, offer a reliable source of knowledge for reasoning. Nevertheless, existing KG-based LLM reasoning methods only treat KGs as factual knowledge bases and overlook the importance of their structural information for reasoning. In this p","authors_text":"Gholamreza Haffari, Linhao Luo, Shirui Pan, Yuan-Fang Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-02T10:14:43Z","title":"Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.01061","kind":"arxiv","version":2},"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":"sha256:498132d21ea9aebd6dea483c7a7a4364651e00ed9efc90d461bbf7b36b4137ec","target":"record","created_at":"2026-07-05T07:48:48Z","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":"cd620357d44a882d0bd3cee5e114b06b5e092895ee078302ca96bdbc0d7b404c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-02T10:14:43Z","title_canon_sha256":"a0e5c39018e599eef7e04ff9bd704890270becd0863c47bba286f4f9b16df26b"},"schema_version":"1.0","source":{"id":"2310.01061","kind":"arxiv","version":2}},"canonical_sha256":"1fd79757527469bd124512e022fb094f06354167ee388f104ec46175f527d673","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1fd79757527469bd124512e022fb094f06354167ee388f104ec46175f527d673","first_computed_at":"2026-07-05T07:48:48.547620Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:48:48.547620Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hd5qXeaJqqilErZJCVplqs3JpehYl9NW6WGVof6TEswn5oFYjOXdj2A8XrQ8KwsZjVKlVMT+YTsOIZ4iZ+voDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:48:48.548045Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.01061","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:498132d21ea9aebd6dea483c7a7a4364651e00ed9efc90d461bbf7b36b4137ec","sha256:0432283152e0e26b493b7896a5f19d7e255b7ca0febac5e53ae3a59af10a3050"],"state_sha256":"229aa99f732c1e048ff1b0fa92239a46c80e735bceabbd23a17c6b63a41f62ff"}