{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LUZMJ7CDCGS62AELRN5GCNKX5U","short_pith_number":"pith:LUZMJ7CD","canonical_record":{"source":{"id":"2508.03820","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-05T18:09:55Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"95995edcb799b15da6a6773473703e5cd0201d64377dbe042b7c1c073a029daf","abstract_canon_sha256":"0c1a0efeb6ec4383f124e1342099926fb32fa9536d4ae8769ea77c06f44aeb51"},"schema_version":"1.0"},"canonical_sha256":"5d32c4fc4311a5ed008b8b7a613557ed03c2e3a3c5002ba8c10910f8022e63cf","source":{"kind":"arxiv","id":"2508.03820","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.03820","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"arxiv_version","alias_value":"2508.03820v1","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.03820","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"pith_short_12","alias_value":"LUZMJ7CDCGS6","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"pith_short_16","alias_value":"LUZMJ7CDCGS62AEL","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"pith_short_8","alias_value":"LUZMJ7CD","created_at":"2026-07-05T11:49:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LUZMJ7CDCGS62AELRN5GCNKX5U","target":"record","payload":{"canonical_record":{"source":{"id":"2508.03820","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-05T18:09:55Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"95995edcb799b15da6a6773473703e5cd0201d64377dbe042b7c1c073a029daf","abstract_canon_sha256":"0c1a0efeb6ec4383f124e1342099926fb32fa9536d4ae8769ea77c06f44aeb51"},"schema_version":"1.0"},"canonical_sha256":"5d32c4fc4311a5ed008b8b7a613557ed03c2e3a3c5002ba8c10910f8022e63cf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:49:15.848302Z","signature_b64":"25PfDMjiqH0gwtkjcfhJNf4uY8K0c5ksJBodJ0T5XZzn5veZO7TekiOxXtcoPNjV7nO5Prv75aUJz1aHZ/NdDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d32c4fc4311a5ed008b8b7a613557ed03c2e3a3c5002ba8c10910f8022e63cf","last_reissued_at":"2026-07-05T11:49:15.847842Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:49:15.847842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.03820","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":"2026-07-05T11:49:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/Wt1TthHp1Qc9XYwUrR+Y7+zrsUo9JJ9m3fbmB4e6aqYCO+QoARaeH+ZaKgu7XLq6vsvrSYJWktEaMuz4RRkBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T10:13:45.242460Z"},"content_sha256":"26f9fd92aa5dfb64817b803c95dedbb53ebe4d6a41c82d12e002de068e7a2eb0","schema_version":"1.0","event_id":"sha256:26f9fd92aa5dfb64817b803c95dedbb53ebe4d6a41c82d12e002de068e7a2eb0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LUZMJ7CDCGS62AELRN5GCNKX5U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bernoulli-LoRA: A Theoretical Framework for Randomized Low-Rank Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.LG","authors_text":"Abdurakhmon Sadiev, Fawaz S Al-Qahtani, Igor Sokolov, Peter Richt\\'arik, Yury Demidovich","submitted_at":"2025-08-05T18:09:55Z","abstract_excerpt":"Parameter-efficient fine-tuning (PEFT) has emerged as a crucial approach for adapting large foundational models to specific tasks, particularly as model sizes continue to grow exponentially. Among PEFT methods, Low-Rank Adaptation (LoRA) (arXiv:2106.09685) stands out for its effectiveness and simplicity, expressing adaptations as a product of two low-rank matrices. While extensive empirical studies demonstrate LoRA's practical utility, theoretical understanding of such methods remains limited. Recent work on RAC-LoRA (arXiv:2410.08305) took initial steps toward rigorous analysis. In this work,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.03820","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/2508.03820/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":"2026-07-05T11:49:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Csiku9i+gIkHQ0uh33rEq7x7PVkbFldtB/QwuWzRBljxoyj7bPKNc/nF40m+qSbWjzcegLhaJ5rb3Bgz1x/ICQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T10:13:45.242990Z"},"content_sha256":"d0b0c7d5d360209a3a3a86498fdfd60d7cad5d0d2e23b2f74da370bbfcc98b4e","schema_version":"1.0","event_id":"sha256:d0b0c7d5d360209a3a3a86498fdfd60d7cad5d0d2e23b2f74da370bbfcc98b4e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LUZMJ7CDCGS62AELRN5GCNKX5U/bundle.json","state_url":"https://pith.science/pith/LUZMJ7CDCGS62AELRN5GCNKX5U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LUZMJ7CDCGS62AELRN5GCNKX5U/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":"2026-08-05T10:13:45Z","links":{"resolver":"https://pith.science/pith/LUZMJ7CDCGS62AELRN5GCNKX5U","bundle":"https://pith.science/pith/LUZMJ7CDCGS62AELRN5GCNKX5U/bundle.json","state":"https://pith.science/pith/LUZMJ7CDCGS62AELRN5GCNKX5U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LUZMJ7CDCGS62AELRN5GCNKX5U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LUZMJ7CDCGS62AELRN5GCNKX5U","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":"0c1a0efeb6ec4383f124e1342099926fb32fa9536d4ae8769ea77c06f44aeb51","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-05T18:09:55Z","title_canon_sha256":"95995edcb799b15da6a6773473703e5cd0201d64377dbe042b7c1c073a029daf"},"schema_version":"1.0","source":{"id":"2508.03820","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.03820","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"arxiv_version","alias_value":"2508.03820v1","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.03820","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"pith_short_12","alias_value":"LUZMJ7CDCGS6","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"pith_short_16","alias_value":"LUZMJ7CDCGS62AEL","created_at":"2026-07-05T11:49:15Z"},{"alias_kind":"pith_short_8","alias_value":"LUZMJ7CD","created_at":"2026-07-05T11:49:15Z"}],"graph_snapshots":[{"event_id":"sha256:d0b0c7d5d360209a3a3a86498fdfd60d7cad5d0d2e23b2f74da370bbfcc98b4e","target":"graph","created_at":"2026-07-05T11:49:15Z","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/2508.03820/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Parameter-efficient fine-tuning (PEFT) has emerged as a crucial approach for adapting large foundational models to specific tasks, particularly as model sizes continue to grow exponentially. Among PEFT methods, Low-Rank Adaptation (LoRA) (arXiv:2106.09685) stands out for its effectiveness and simplicity, expressing adaptations as a product of two low-rank matrices. While extensive empirical studies demonstrate LoRA's practical utility, theoretical understanding of such methods remains limited. Recent work on RAC-LoRA (arXiv:2410.08305) took initial steps toward rigorous analysis. In this work,","authors_text":"Abdurakhmon Sadiev, Fawaz S Al-Qahtani, Igor Sokolov, Peter Richt\\'arik, Yury Demidovich","cross_cats":["math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-05T18:09:55Z","title":"Bernoulli-LoRA: A Theoretical Framework for Randomized Low-Rank Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.03820","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":"sha256:26f9fd92aa5dfb64817b803c95dedbb53ebe4d6a41c82d12e002de068e7a2eb0","target":"record","created_at":"2026-07-05T11:49:15Z","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":"0c1a0efeb6ec4383f124e1342099926fb32fa9536d4ae8769ea77c06f44aeb51","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-05T18:09:55Z","title_canon_sha256":"95995edcb799b15da6a6773473703e5cd0201d64377dbe042b7c1c073a029daf"},"schema_version":"1.0","source":{"id":"2508.03820","kind":"arxiv","version":1}},"canonical_sha256":"5d32c4fc4311a5ed008b8b7a613557ed03c2e3a3c5002ba8c10910f8022e63cf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d32c4fc4311a5ed008b8b7a613557ed03c2e3a3c5002ba8c10910f8022e63cf","first_computed_at":"2026-07-05T11:49:15.847842Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:49:15.847842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"25PfDMjiqH0gwtkjcfhJNf4uY8K0c5ksJBodJ0T5XZzn5veZO7TekiOxXtcoPNjV7nO5Prv75aUJz1aHZ/NdDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:49:15.848302Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.03820","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:26f9fd92aa5dfb64817b803c95dedbb53ebe4d6a41c82d12e002de068e7a2eb0","sha256:d0b0c7d5d360209a3a3a86498fdfd60d7cad5d0d2e23b2f74da370bbfcc98b4e"],"state_sha256":"d1e4bd89e8ac61fb9c959b9df02bc610b67792e565494c4ccdb483fa5eb4354c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ovY4MXa3vLySSLSs10e8I74iFYsx0RTIpDfO9xEhXAi9ym5CuRGJTmkXDDC6xQ/yFMcIcH8CEE/AcrGjZtrFDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T10:13:45.246543Z","bundle_sha256":"b8b2575853c9ca0210e52b152ca32a50b497299630a0c2351ec231d5f40a28d6"}}