{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:BK7NN4IKSOH4WP47XFFGKH2GYE","short_pith_number":"pith:BK7NN4IK","schema_version":"1.0","canonical_sha256":"0abed6f10a938fcb3f9fb94a651f46c10ebce2fca2688817c3f1e612aadb171d","source":{"kind":"arxiv","id":"2307.12057","version":2},"attestation_state":"computed","paper":{"title":"External Reasoning: Towards Multi-Large-Language-Models Interchangeable Assistance with Human Feedback","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Akide Liu","submitted_at":"2023-07-05T17:05:32Z","abstract_excerpt":"Memory is identified as a crucial human faculty that allows for the retention of visual and linguistic information within the hippocampus and neurons in the brain, which can subsequently be retrieved to address real-world challenges that arise through a lifetime of learning. The resolution of complex AI tasks through the application of acquired knowledge represents a stride toward the realization of artificial general intelligence. However, despite the prevalence of Large Language Models (LLMs) like GPT-3.5 and GPT-4 \\cite{brown2020language, leiter2023chatgpt, zaitsu2023distinguishing, OpenAI2"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2307.12057","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-07-05T17:05:32Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"923102104eb2f68c54f8d787e15b012513e2e25a22b28e45f088cbe89f787957","abstract_canon_sha256":"dfd0c552b25d4a93b284fe746da19fec48b48f0defefe54a1ca012bcedcd5aa3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:44:50.585052Z","signature_b64":"uQMEZzKO96YoGVXMGF95Un+3k2ll5CMdytS3zFoyN0CoYDusiOaOL7oLz5qRhdzMFx5gdw0x6EusgMZDb1ppAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0abed6f10a938fcb3f9fb94a651f46c10ebce2fca2688817c3f1e612aadb171d","last_reissued_at":"2026-07-05T06:44:50.584526Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:44:50.584526Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"External Reasoning: Towards Multi-Large-Language-Models Interchangeable Assistance with Human Feedback","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Akide Liu","submitted_at":"2023-07-05T17:05:32Z","abstract_excerpt":"Memory is identified as a crucial human faculty that allows for the retention of visual and linguistic information within the hippocampus and neurons in the brain, which can subsequently be retrieved to address real-world challenges that arise through a lifetime of learning. The resolution of complex AI tasks through the application of acquired knowledge represents a stride toward the realization of artificial general intelligence. However, despite the prevalence of Large Language Models (LLMs) like GPT-3.5 and GPT-4 \\cite{brown2020language, leiter2023chatgpt, zaitsu2023distinguishing, OpenAI2"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.12057","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2307.12057/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2307.12057","created_at":"2026-07-05T06:44:50.584582+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.12057v2","created_at":"2026-07-05T06:44:50.584582+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.12057","created_at":"2026-07-05T06:44:50.584582+00:00"},{"alias_kind":"pith_short_12","alias_value":"BK7NN4IKSOH4","created_at":"2026-07-05T06:44:50.584582+00:00"},{"alias_kind":"pith_short_16","alias_value":"BK7NN4IKSOH4WP47","created_at":"2026-07-05T06:44:50.584582+00:00"},{"alias_kind":"pith_short_8","alias_value":"BK7NN4IK","created_at":"2026-07-05T06:44:50.584582+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2506.00309","citing_title":"Evaluation of LLMs for mathematical problem solving","ref_index":87,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE","json":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE.json","graph_json":"https://pith.science/api/pith-number/BK7NN4IKSOH4WP47XFFGKH2GYE/graph.json","events_json":"https://pith.science/api/pith-number/BK7NN4IKSOH4WP47XFFGKH2GYE/events.json","paper":"https://pith.science/paper/BK7NN4IK"},"agent_actions":{"view_html":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE","download_json":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE.json","view_paper":"https://pith.science/paper/BK7NN4IK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.12057&json=true","fetch_graph":"https://pith.science/api/pith-number/BK7NN4IKSOH4WP47XFFGKH2GYE/graph.json","fetch_events":"https://pith.science/api/pith-number/BK7NN4IKSOH4WP47XFFGKH2GYE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE/action/storage_attestation","attest_author":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE/action/author_attestation","sign_citation":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE/action/citation_signature","submit_replication":"https://pith.science/pith/BK7NN4IKSOH4WP47XFFGKH2GYE/action/replication_record"}},"created_at":"2026-07-05T06:44:50.584582+00:00","updated_at":"2026-07-05T06:44:50.584582+00:00"}