{"paper":{"title":"Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"RILKE lets LLMs receive lifelong knowledge updates by intervening in representation space with localized modules.","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Haifeng Chen, Haoyu Wang, Shengyu Chen, Xinshuai Dong, Xujiang Zhao, Xuyuan Liu, Yanchi Liu, Yujun Yan, Zhengzhang Chen","submitted_at":"2025-11-25T22:15:00Z","abstract_excerpt":"Large language models (LLMs) often produce incorrect or outdated content after being employed. Efficient and accurate knowledge updates without costly retraining are a major challenge. This problem is particularly challenging in lifelong settings, where complex, unstructured knowledge must coexist without interference. We introduce RILKE (Representation Intervention for Lifelong KnowledgE Control), a robust and scalable method that treats knowledge control as interventions within the model's representation space. Leveraging representation-space expressiveness, we identify two key properties en"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"RILKE scales effectively to large-scale benchmarks, demonstrating high edit success and strong paraphrase generalization while preserving general utility with modest memory overhead.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The assumption that two key properties of the representation space enable fine-grained control over complex unstructured knowledge without cross-edit interference or loss of general utility when base weights remain frozen.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"RILKE learns low-dimensional, paraphrase-robust modules in LLM representation space that enable interference-free lifelong knowledge edits while preserving base model utility.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"RILKE lets LLMs receive lifelong knowledge updates by intervening in representation space with localized modules.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"a220710c434dc41969f6858c8dff992f2eaabf5890361dc2d3a5cbdb401d50dc"},"source":{"id":"2511.20892","kind":"arxiv","version":4},"verdict":{"id":"4b85b87a-e8e2-4841-b348-1874e32e2db6","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-17T04:22:07.604370Z","strongest_claim":"RILKE scales effectively to large-scale benchmarks, demonstrating high edit success and strong paraphrase generalization while preserving general utility with modest memory overhead.","one_line_summary":"RILKE learns low-dimensional, paraphrase-robust modules in LLM representation space that enable interference-free lifelong knowledge edits while preserving base model utility.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The assumption that two key properties of the representation space enable fine-grained control over complex unstructured knowledge without cross-edit interference or loss of general utility when base weights remain frozen.","pith_extraction_headline":"RILKE lets LLMs receive lifelong knowledge updates by intervening in representation space with localized modules."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2511.20892/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":2,"snapshot_sha256":"6aee000496072c85e7ad6bcaffe21f4cf7c25b4fe691c655a04ae9aff238a37f"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}