{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:W3452QNA5CYRVOKPNN7RX7VFQE","short_pith_number":"pith:W3452QNA","schema_version":"1.0","canonical_sha256":"b6f9dd41a0e8b11ab94f6b7f1bfea58135af3b8199754e3af9de152753450694","source":{"kind":"arxiv","id":"2507.18178","version":1},"attestation_state":"computed","paper":{"title":"Decoupling Knowledge and Reasoning in LLMs: An Exploration Using Cognitive Dual-System Theory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jiandong Gao, Ji Wu, Mutian Yang","submitted_at":"2025-07-24T08:24:52Z","abstract_excerpt":"While large language models (LLMs) leverage both knowledge and reasoning during inference, the capacity to distinguish between them plays a pivotal role in model analysis, interpretability, and development. Inspired by dual-system cognitive theory, we propose a cognition attribution framework to decouple the contribution of knowledge and reasoning. In particular, the cognition of LLMs is decomposed into two distinct yet complementary phases: knowledge retrieval (Phase 1) and reasoning adjustment (Phase 2). To separate these phases, LLMs are prompted to generate answers under two different cogn"},"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":"2507.18178","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-07-24T08:24:52Z","cross_cats_sorted":[],"title_canon_sha256":"6208e3ef3acaeb5d69eb327e89e571026f388407178ad7b907e8269ccb151514","abstract_canon_sha256":"9ec3179fdfc155acd84f7eca25bbecaa418765f8de81a009b8080689aff03b0d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:42:43.218081Z","signature_b64":"8ZIERHwlIYDu0eLjtCFbM7Y0Q4qH2sRZv8Nm70a8CHER+5he4coaVy4YPMY5/I80oaWg96bIuNpow8C3YwF4Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6f9dd41a0e8b11ab94f6b7f1bfea58135af3b8199754e3af9de152753450694","last_reissued_at":"2026-07-05T11:42:43.217665Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:42:43.217665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Decoupling Knowledge and Reasoning in LLMs: An Exploration Using Cognitive Dual-System Theory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jiandong Gao, Ji Wu, Mutian Yang","submitted_at":"2025-07-24T08:24:52Z","abstract_excerpt":"While large language models (LLMs) leverage both knowledge and reasoning during inference, the capacity to distinguish between them plays a pivotal role in model analysis, interpretability, and development. Inspired by dual-system cognitive theory, we propose a cognition attribution framework to decouple the contribution of knowledge and reasoning. In particular, the cognition of LLMs is decomposed into two distinct yet complementary phases: knowledge retrieval (Phase 1) and reasoning adjustment (Phase 2). To separate these phases, LLMs are prompted to generate answers under two different cogn"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.18178","kind":"arxiv","version":1},"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/2507.18178/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":"2507.18178","created_at":"2026-07-05T11:42:43.217721+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.18178v1","created_at":"2026-07-05T11:42:43.217721+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.18178","created_at":"2026-07-05T11:42:43.217721+00:00"},{"alias_kind":"pith_short_12","alias_value":"W3452QNA5CYR","created_at":"2026-07-05T11:42:43.217721+00:00"},{"alias_kind":"pith_short_16","alias_value":"W3452QNA5CYRVOKP","created_at":"2026-07-05T11:42:43.217721+00:00"},{"alias_kind":"pith_short_8","alias_value":"W3452QNA","created_at":"2026-07-05T11:42:43.217721+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE","json":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE.json","graph_json":"https://pith.science/api/pith-number/W3452QNA5CYRVOKPNN7RX7VFQE/graph.json","events_json":"https://pith.science/api/pith-number/W3452QNA5CYRVOKPNN7RX7VFQE/events.json","paper":"https://pith.science/paper/W3452QNA"},"agent_actions":{"view_html":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE","download_json":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE.json","view_paper":"https://pith.science/paper/W3452QNA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.18178&json=true","fetch_graph":"https://pith.science/api/pith-number/W3452QNA5CYRVOKPNN7RX7VFQE/graph.json","fetch_events":"https://pith.science/api/pith-number/W3452QNA5CYRVOKPNN7RX7VFQE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE/action/storage_attestation","attest_author":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE/action/author_attestation","sign_citation":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE/action/citation_signature","submit_replication":"https://pith.science/pith/W3452QNA5CYRVOKPNN7RX7VFQE/action/replication_record"}},"created_at":"2026-07-05T11:42:43.217721+00:00","updated_at":"2026-07-05T11:42:43.217721+00:00"}