{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:QDXS5SC4KLIRYLQMO52BE5RWK5","short_pith_number":"pith:QDXS5SC4","schema_version":"1.0","canonical_sha256":"80ef2ec85c52d11c2e0c777412763657564dd59b4f0d420095a157c37a4ab1f4","source":{"kind":"arxiv","id":"2412.11536","version":1},"attestation_state":"computed","paper":{"title":"Let your LLM generate a few tokens and you will reduce the need for retrieval","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Herv\\'e D\\'ejean","submitted_at":"2024-12-16T08:13:14Z","abstract_excerpt":"In this paper, we investigate how efficiently large language models (LLM) can be trained to check whether an answer is already stored in their parametric memory. We distill an LLM-as-a-judge to compute the IK (I Know) score. We found that this method is particularly beneficial in the context of retrieval-assisted augmented generation (RAG), with a respectable accuracy of 80%. It enables a significant reduction (more than 50%) in the number of search and reranking steps required for certain data sets. We have also introduced the IK score, which serves as a useful tool for characterising dataset"},"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":"2412.11536","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-16T08:13:14Z","cross_cats_sorted":[],"title_canon_sha256":"e73b4249219c4b1ce255832050408aaa90fa1a1ed0b199cf16426ebd5ab6e2fe","abstract_canon_sha256":"03c716b957b77f0e3fa16b73a49a5b2b03dd89c9a1ce7a0c101f7c16e1c82268"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:49:34.356635Z","signature_b64":"jicBCJZ3jXZe1Z3W5jtySb0HIzAkQt627ACJDNT/4tL73yMnajuBlbKFyMh/gReCUshCPklehqUM12ifvlcAAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"80ef2ec85c52d11c2e0c777412763657564dd59b4f0d420095a157c37a4ab1f4","last_reissued_at":"2026-07-05T09:49:34.356176Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:49:34.356176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Let your LLM generate a few tokens and you will reduce the need for retrieval","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Herv\\'e D\\'ejean","submitted_at":"2024-12-16T08:13:14Z","abstract_excerpt":"In this paper, we investigate how efficiently large language models (LLM) can be trained to check whether an answer is already stored in their parametric memory. We distill an LLM-as-a-judge to compute the IK (I Know) score. We found that this method is particularly beneficial in the context of retrieval-assisted augmented generation (RAG), with a respectable accuracy of 80%. It enables a significant reduction (more than 50%) in the number of search and reranking steps required for certain data sets. We have also introduced the IK score, which serves as a useful tool for characterising dataset"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11536","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/2412.11536/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":"2412.11536","created_at":"2026-07-05T09:49:34.356234+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.11536v1","created_at":"2026-07-05T09:49:34.356234+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11536","created_at":"2026-07-05T09:49:34.356234+00:00"},{"alias_kind":"pith_short_12","alias_value":"QDXS5SC4KLIR","created_at":"2026-07-05T09:49:34.356234+00:00"},{"alias_kind":"pith_short_16","alias_value":"QDXS5SC4KLIRYLQM","created_at":"2026-07-05T09:49:34.356234+00:00"},{"alias_kind":"pith_short_8","alias_value":"QDXS5SC4","created_at":"2026-07-05T09:49:34.356234+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/QDXS5SC4KLIRYLQMO52BE5RWK5","json":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5.json","graph_json":"https://pith.science/api/pith-number/QDXS5SC4KLIRYLQMO52BE5RWK5/graph.json","events_json":"https://pith.science/api/pith-number/QDXS5SC4KLIRYLQMO52BE5RWK5/events.json","paper":"https://pith.science/paper/QDXS5SC4"},"agent_actions":{"view_html":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5","download_json":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5.json","view_paper":"https://pith.science/paper/QDXS5SC4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.11536&json=true","fetch_graph":"https://pith.science/api/pith-number/QDXS5SC4KLIRYLQMO52BE5RWK5/graph.json","fetch_events":"https://pith.science/api/pith-number/QDXS5SC4KLIRYLQMO52BE5RWK5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5/action/storage_attestation","attest_author":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5/action/author_attestation","sign_citation":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5/action/citation_signature","submit_replication":"https://pith.science/pith/QDXS5SC4KLIRYLQMO52BE5RWK5/action/replication_record"}},"created_at":"2026-07-05T09:49:34.356234+00:00","updated_at":"2026-07-05T09:49:34.356234+00:00"}