{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CAA5K3D2YKLTK57QGRZMDDSPET","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":"61dfc18c0b3a11e47865cf8708a8a9329b1118f0d087bd6b67671e3d5fef991d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-16T07:23:59Z","title_canon_sha256":"ef0c33c89ba831b2b70b9e516f6c1f2dba6ac330b9fcdf036ef49b065a25ed55"},"schema_version":"1.0","source":{"id":"2505.10939","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.10939","created_at":"2026-07-05T11:48:03Z"},{"alias_kind":"arxiv_version","alias_value":"2505.10939v2","created_at":"2026-07-05T11:48:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.10939","created_at":"2026-07-05T11:48:03Z"},{"alias_kind":"pith_short_12","alias_value":"CAA5K3D2YKLT","created_at":"2026-07-05T11:48:03Z"},{"alias_kind":"pith_short_16","alias_value":"CAA5K3D2YKLTK57Q","created_at":"2026-07-05T11:48:03Z"},{"alias_kind":"pith_short_8","alias_value":"CAA5K3D2","created_at":"2026-07-05T11:48:03Z"}],"graph_snapshots":[{"event_id":"sha256:32cc4bf552e998fba90288674edabf4d343a4a461fe4ca4a3d50a23f50493469","target":"graph","created_at":"2026-07-05T11:48:03Z","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/2505.10939/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models often struggle with zero-shot generalization, and several modular approaches have been proposed to address this challenge. Yet, we hypothesize that a key limitation remains: the entanglement of general knowledge and task-specific adaptations. To overcome this, we propose a modular framework that disentangles these components by constructing a library of task-specific LoRA modules alongside a general-domain LoRA. By subtracting this general knowledge component from each task-specific module, we obtain residual modules that focus more exclusively on task-relevant informatio","authors_text":"Ali Edalat, Mohammadtaha Bagherifard, Sahar Rajabi, Yadollah Yaghoobzadeh","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-16T07:23:59Z","title":"GenKnowSub: Improving Modularity and Reusability of LLMs through General Knowledge Subtraction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.10939","kind":"arxiv","version":2},"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":"sha256:035298300b486c00c43c995783065e501aba0c2b339cd3d22d7d1351bac58c52","target":"record","created_at":"2026-07-05T11:48:03Z","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":"61dfc18c0b3a11e47865cf8708a8a9329b1118f0d087bd6b67671e3d5fef991d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-16T07:23:59Z","title_canon_sha256":"ef0c33c89ba831b2b70b9e516f6c1f2dba6ac330b9fcdf036ef49b065a25ed55"},"schema_version":"1.0","source":{"id":"2505.10939","kind":"arxiv","version":2}},"canonical_sha256":"1001d56c7ac2973577f03472c18e4f24f3907852cd23dc6f0ca18b864980990d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1001d56c7ac2973577f03472c18e4f24f3907852cd23dc6f0ca18b864980990d","first_computed_at":"2026-07-05T11:48:03.674304Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:48:03.674304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y6nMnZ0egswDeB4ZRv5uLkfhighdkHZ8k7xM2YCr5e6T43sZU1buzWOcrZXj4zwUU182sLS43XBGg3WvyZ4AAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:48:03.674887Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.10939","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:035298300b486c00c43c995783065e501aba0c2b339cd3d22d7d1351bac58c52","sha256:32cc4bf552e998fba90288674edabf4d343a4a461fe4ca4a3d50a23f50493469"],"state_sha256":"a7ba7d6cb1b1e13bee781b2e596005d5f825a35acce28843eec39c672438a420"}