{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CLX7I4MYV2QA4P5CMZTTAIJ22Y","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":"ee9cfa043f8233f4283f51920a0f38c1834f94d03e48759ba04ec68bbef8f68c","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2025-05-13T23:57:02Z","title_canon_sha256":"6775f9b10de98f0410099ad85b31dea95a00fdba6819e3e3f030ca03c14890d8"},"schema_version":"1.0","source":{"id":"2505.09031","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.09031","created_at":"2026-07-05T11:02:49Z"},{"alias_kind":"arxiv_version","alias_value":"2505.09031v1","created_at":"2026-07-05T11:02:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.09031","created_at":"2026-07-05T11:02:49Z"},{"alias_kind":"pith_short_12","alias_value":"CLX7I4MYV2QA","created_at":"2026-07-05T11:02:49Z"},{"alias_kind":"pith_short_16","alias_value":"CLX7I4MYV2QA4P5C","created_at":"2026-07-05T11:02:49Z"},{"alias_kind":"pith_short_8","alias_value":"CLX7I4MY","created_at":"2026-07-05T11:02:49Z"}],"graph_snapshots":[{"event_id":"sha256:83fedf0a29acd9af8acd8a6a20594c821cae940e65c3c4fb2d804850c62aa1e7","target":"graph","created_at":"2026-07-05T11:02:49Z","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/2505.09031/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hallucination, where large language models (LLMs) generate confident but incorrect or irrelevant information, remains a key limitation in their application to complex, open-ended tasks. Chain-of-thought (CoT) prompting has emerged as a promising method for improving multistep reasoning by guiding models through intermediate steps. However, CoT alone does not fully address the hallucination problem. In this work, we investigate how combining CoT with retrieval-augmented generation (RAG), as well as applying self-consistency and self-verification strategies, can reduce hallucinations and improve","authors_text":"Adarsh Kumar, Hwiyoon Kim, Jawahar Sai Nathani, Neil Roy","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2025-05-13T23:57:02Z","title":"Improving the Reliability of LLMs: Combining CoT, RAG, Self-Consistency, and Self-Verification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.09031","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":"sha256:1da3553e5d03c49704084b5671395f61e7d1f7ac5b619ee0c8e886495acba983","target":"record","created_at":"2026-07-05T11:02:49Z","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":"ee9cfa043f8233f4283f51920a0f38c1834f94d03e48759ba04ec68bbef8f68c","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2025-05-13T23:57:02Z","title_canon_sha256":"6775f9b10de98f0410099ad85b31dea95a00fdba6819e3e3f030ca03c14890d8"},"schema_version":"1.0","source":{"id":"2505.09031","kind":"arxiv","version":1}},"canonical_sha256":"12eff47198aea00e3fa2666730213ad60ebf6031e00052fb87af251e2f04e097","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"12eff47198aea00e3fa2666730213ad60ebf6031e00052fb87af251e2f04e097","first_computed_at":"2026-07-05T11:02:49.183136Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:02:49.183136Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SUB/rLQgwp57AfQ/hORghoFRhKCYDoDEOg2dF43be7baQ772HEwtk7C5BXjHfsnhUegJCMhncpK6xiNi7jVnBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:02:49.183621Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.09031","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1da3553e5d03c49704084b5671395f61e7d1f7ac5b619ee0c8e886495acba983","sha256:83fedf0a29acd9af8acd8a6a20594c821cae940e65c3c4fb2d804850c62aa1e7"],"state_sha256":"f8cc8c1019ab86f7e1a0cef880778e5cfe823afbe1522b3f4083d7cb4ab0f797"}