{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:2A3SG3QRTBYUZCCZXVD2WVESTC","short_pith_number":"pith:2A3SG3QR","canonical_record":{"source":{"id":"2607.21612","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T17:06:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"efb3b9e5fe09adc2a625f4f09a1817f67abbde0eb93f74a20e422f8d01668897","abstract_canon_sha256":"331f64381046b1cabdaf581892862cce8d9aab24ef35d0d9b706bc499bf14fde"},"schema_version":"1.0"},"canonical_sha256":"d037236e1198714c8859bd47ab549298803a4fb6094f0ef9583849f02bd8d2f9","source":{"kind":"arxiv","id":"2607.21612","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.21612","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"arxiv_version","alias_value":"2607.21612v1","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.21612","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"pith_short_12","alias_value":"2A3SG3QRTBYU","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"pith_short_16","alias_value":"2A3SG3QRTBYUZCCZ","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"pith_short_8","alias_value":"2A3SG3QR","created_at":"2026-07-27T00:20:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:2A3SG3QRTBYUZCCZXVD2WVESTC","target":"record","payload":{"canonical_record":{"source":{"id":"2607.21612","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T17:06:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"efb3b9e5fe09adc2a625f4f09a1817f67abbde0eb93f74a20e422f8d01668897","abstract_canon_sha256":"331f64381046b1cabdaf581892862cce8d9aab24ef35d0d9b706bc499bf14fde"},"schema_version":"1.0"},"canonical_sha256":"d037236e1198714c8859bd47ab549298803a4fb6094f0ef9583849f02bd8d2f9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-27T00:20:11.065640Z","signature_b64":"8ya7NUAOPE/KlJi3JVwSzyjHCx6axttz65kKMeijdKuf/ZiJl2Fjt7jqgWrmu+mUwk05SmqU5fqF3pcXm9JJCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d037236e1198714c8859bd47ab549298803a4fb6094f0ef9583849f02bd8d2f9","last_reissued_at":"2026-07-27T00:20:11.064803Z","signature_status":"signed_v1","first_computed_at":"2026-07-27T00:20:11.064803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.21612","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-27T00:20:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LQhkMOKaqje1ddtEQWhfsnldv9FtCZQiS5zwaGzaoL0n3huj6Gdau4kj4NqVey+mnxq60zhyEfRi5f9UDdJJBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T09:14:01.252255Z"},"content_sha256":"74651d31b449ee490072440aa445a6b9dddbf11d9612c964a4eb21bee9a485a8","schema_version":"1.0","event_id":"sha256:74651d31b449ee490072440aa445a6b9dddbf11d9612c964a4eb21bee9a485a8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:2A3SG3QRTBYUZCCZXVD2WVESTC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Procedural Knowledge Is Not Low-Rank: Why LoRA Fails to Internalize Multi-Step Procedures","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Hao Guo, Kevin Shabahang, Rivaan Patil, Simon Dennis","submitted_at":"2026-05-23T17:06:02Z","abstract_excerpt":"Parameter-efficient fine-tuning methods like LoRA have become the default for adapting large language models, succeeding across instruction following, style transfer, and factual adaptation. We show that for procedural knowledge--the ability to follow multi-step procedures with conditional branching through to terminal states--LoRA fails to match full fine-tuning at the ranks where it retains its efficiency advantage. In a systematic ablation (r = 16--128) on a procedural travel booking task (14 nodes), all LoRA configurations fail uniformly (task success <= 2.54 vs. 4.11 for full fine-tuning,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.21612","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/2607.21612/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-27T00:20:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iEcEiGFyhe4PMzyxawWznnQtYO25MRLwlT+zrGz1K56fRjCo/IVOotBZ14J42Wg3praPNX0sbtPiAg19rCRyBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T09:14:01.252864Z"},"content_sha256":"493df1b3bb63341da45abdc09a1276677207444a2e687bb3a9157db977243281","schema_version":"1.0","event_id":"sha256:493df1b3bb63341da45abdc09a1276677207444a2e687bb3a9157db977243281"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2A3SG3QRTBYUZCCZXVD2WVESTC/bundle.json","state_url":"https://pith.science/pith/2A3SG3QRTBYUZCCZXVD2WVESTC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2A3SG3QRTBYUZCCZXVD2WVESTC/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T09:14:01Z","links":{"resolver":"https://pith.science/pith/2A3SG3QRTBYUZCCZXVD2WVESTC","bundle":"https://pith.science/pith/2A3SG3QRTBYUZCCZXVD2WVESTC/bundle.json","state":"https://pith.science/pith/2A3SG3QRTBYUZCCZXVD2WVESTC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2A3SG3QRTBYUZCCZXVD2WVESTC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2A3SG3QRTBYUZCCZXVD2WVESTC","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":"331f64381046b1cabdaf581892862cce8d9aab24ef35d0d9b706bc499bf14fde","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T17:06:02Z","title_canon_sha256":"efb3b9e5fe09adc2a625f4f09a1817f67abbde0eb93f74a20e422f8d01668897"},"schema_version":"1.0","source":{"id":"2607.21612","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.21612","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"arxiv_version","alias_value":"2607.21612v1","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.21612","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"pith_short_12","alias_value":"2A3SG3QRTBYU","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"pith_short_16","alias_value":"2A3SG3QRTBYUZCCZ","created_at":"2026-07-27T00:20:11Z"},{"alias_kind":"pith_short_8","alias_value":"2A3SG3QR","created_at":"2026-07-27T00:20:11Z"}],"graph_snapshots":[{"event_id":"sha256:493df1b3bb63341da45abdc09a1276677207444a2e687bb3a9157db977243281","target":"graph","created_at":"2026-07-27T00:20:11Z","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/2607.21612/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Parameter-efficient fine-tuning methods like LoRA have become the default for adapting large language models, succeeding across instruction following, style transfer, and factual adaptation. We show that for procedural knowledge--the ability to follow multi-step procedures with conditional branching through to terminal states--LoRA fails to match full fine-tuning at the ranks where it retains its efficiency advantage. In a systematic ablation (r = 16--128) on a procedural travel booking task (14 nodes), all LoRA configurations fail uniformly (task success <= 2.54 vs. 4.11 for full fine-tuning,","authors_text":"Hao Guo, Kevin Shabahang, Rivaan Patil, Simon Dennis","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T17:06:02Z","title":"Procedural Knowledge Is Not Low-Rank: Why LoRA Fails to Internalize Multi-Step Procedures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.21612","kind":"arxiv","version":1},"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":"sha256:74651d31b449ee490072440aa445a6b9dddbf11d9612c964a4eb21bee9a485a8","target":"record","created_at":"2026-07-27T00:20:11Z","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":"331f64381046b1cabdaf581892862cce8d9aab24ef35d0d9b706bc499bf14fde","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T17:06:02Z","title_canon_sha256":"efb3b9e5fe09adc2a625f4f09a1817f67abbde0eb93f74a20e422f8d01668897"},"schema_version":"1.0","source":{"id":"2607.21612","kind":"arxiv","version":1}},"canonical_sha256":"d037236e1198714c8859bd47ab549298803a4fb6094f0ef9583849f02bd8d2f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d037236e1198714c8859bd47ab549298803a4fb6094f0ef9583849f02bd8d2f9","first_computed_at":"2026-07-27T00:20:11.064803Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-27T00:20:11.064803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8ya7NUAOPE/KlJi3JVwSzyjHCx6axttz65kKMeijdKuf/ZiJl2Fjt7jqgWrmu+mUwk05SmqU5fqF3pcXm9JJCg==","signature_status":"signed_v1","signed_at":"2026-07-27T00:20:11.065640Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.21612","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:74651d31b449ee490072440aa445a6b9dddbf11d9612c964a4eb21bee9a485a8","sha256:493df1b3bb63341da45abdc09a1276677207444a2e687bb3a9157db977243281"],"state_sha256":"cffcc0b951ca4144a6625d762db1994b89803e80f4ab87f055b8ff5f7e8230b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"975YASmffP8Ao96+ZCFYmJ+v6DktP4da9ZrByp98sFAR4PAz9JiDA4aHVmqfyBhazf8t2RtyevvIfYLcPuzcAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T09:14:01.256395Z","bundle_sha256":"785e19bafa66182f6bd429551e2f257c409d20cfbea0a04793f5ed2e324d16ec"}}