{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4ZX3BY4SOEW7JG7ZO7JJWSZX2Y","short_pith_number":"pith:4ZX3BY4S","canonical_record":{"source":{"id":"2411.07806","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-12T14:01:08Z","cross_cats_sorted":["cs.CR","eess.SP"],"title_canon_sha256":"ec9ace684a1e167c97bcda091676679ea385412cc0e5eec8b2b21040b82aa13a","abstract_canon_sha256":"9dbf254fecf19d632d346220a08f9694aa440fdac3b32f200bd79fd833176e7b"},"schema_version":"1.0"},"canonical_sha256":"e66fb0e392712df49bf977d29b4b37d63575b7f471860c8d4ab7d426ff6694d0","source":{"kind":"arxiv","id":"2411.07806","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.07806","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"arxiv_version","alias_value":"2411.07806v2","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.07806","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"pith_short_12","alias_value":"4ZX3BY4SOEW7","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"pith_short_16","alias_value":"4ZX3BY4SOEW7JG7Z","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"pith_short_8","alias_value":"4ZX3BY4S","created_at":"2026-07-05T09:41:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4ZX3BY4SOEW7JG7ZO7JJWSZX2Y","target":"record","payload":{"canonical_record":{"source":{"id":"2411.07806","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-12T14:01:08Z","cross_cats_sorted":["cs.CR","eess.SP"],"title_canon_sha256":"ec9ace684a1e167c97bcda091676679ea385412cc0e5eec8b2b21040b82aa13a","abstract_canon_sha256":"9dbf254fecf19d632d346220a08f9694aa440fdac3b32f200bd79fd833176e7b"},"schema_version":"1.0"},"canonical_sha256":"e66fb0e392712df49bf977d29b4b37d63575b7f471860c8d4ab7d426ff6694d0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:41:03.479973Z","signature_b64":"WSxGhbsULp8WoRQR+Yml/MPp/Bh2UQEAmB50tYXHfsOjspkauy3NuK3sZhMIgtq+gOAeJRMzbM5BQqEZcOOrCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e66fb0e392712df49bf977d29b4b37d63575b7f471860c8d4ab7d426ff6694d0","last_reissued_at":"2026-07-05T09:41:03.479524Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:41:03.479524Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.07806","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:41:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i+qKnIklx9cILWeof5i713sSzZQ5kW3Ibc9kQu2lG06r4SV+h7aGzksUOJYPbiZnHOoCfd7qqg73iLRHYTMYBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:07:54.565494Z"},"content_sha256":"87890fdd48c9a8ab420e341773aa4e578c40bd1c53ea6d4c99b1466a82a544f9","schema_version":"1.0","event_id":"sha256:87890fdd48c9a8ab420e341773aa4e578c40bd1c53ea6d4c99b1466a82a544f9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4ZX3BY4SOEW7JG7ZO7JJWSZX2Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","eess.SP"],"primary_cat":"cs.LG","authors_text":"Hengtao He, Jun Zhang, Khaled B. Letaief, Shenghui Song, Tianqu Kang, Zixin Wang","submitted_at":"2024-11-12T14:01:08Z","abstract_excerpt":"Fine-tuning large pre-trained foundation models (FMs) on distributed edge devices presents considerable computational and privacy challenges. Federated fine-tuning (FedFT) mitigates some privacy issues by facilitating collaborative model training without the need to share raw data. To lessen the computational burden on resource-limited devices, combining low-rank adaptation (LoRA) with federated learning enables parameter-efficient fine-tuning. Additionally, the split FedFT architecture partitions an FM between edge devices and a central server, reducing the necessity for complete model deploy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.07806","kind":"arxiv","version":2},"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/2411.07806/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":"2026-07-05T09:41:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"prm5ANUsLcuzkBFU7EqFIosa4q3Dnz1GUPTv7oIW4KHy3j1Ob/530QVRLhYvEQMAdwnck1qARyn8ICenrPS9DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:07:54.566015Z"},"content_sha256":"d766df7f73cc698932d43cc703242a59f64b2103a1aaae345bb0e8fb771b3794","schema_version":"1.0","event_id":"sha256:d766df7f73cc698932d43cc703242a59f64b2103a1aaae345bb0e8fb771b3794"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4ZX3BY4SOEW7JG7ZO7JJWSZX2Y/bundle.json","state_url":"https://pith.science/pith/4ZX3BY4SOEW7JG7ZO7JJWSZX2Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4ZX3BY4SOEW7JG7ZO7JJWSZX2Y/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":"2026-08-06T12:07:54Z","links":{"resolver":"https://pith.science/pith/4ZX3BY4SOEW7JG7ZO7JJWSZX2Y","bundle":"https://pith.science/pith/4ZX3BY4SOEW7JG7ZO7JJWSZX2Y/bundle.json","state":"https://pith.science/pith/4ZX3BY4SOEW7JG7ZO7JJWSZX2Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4ZX3BY4SOEW7JG7ZO7JJWSZX2Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4ZX3BY4SOEW7JG7ZO7JJWSZX2Y","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":"9dbf254fecf19d632d346220a08f9694aa440fdac3b32f200bd79fd833176e7b","cross_cats_sorted":["cs.CR","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-12T14:01:08Z","title_canon_sha256":"ec9ace684a1e167c97bcda091676679ea385412cc0e5eec8b2b21040b82aa13a"},"schema_version":"1.0","source":{"id":"2411.07806","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.07806","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"arxiv_version","alias_value":"2411.07806v2","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.07806","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"pith_short_12","alias_value":"4ZX3BY4SOEW7","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"pith_short_16","alias_value":"4ZX3BY4SOEW7JG7Z","created_at":"2026-07-05T09:41:03Z"},{"alias_kind":"pith_short_8","alias_value":"4ZX3BY4S","created_at":"2026-07-05T09:41:03Z"}],"graph_snapshots":[{"event_id":"sha256:d766df7f73cc698932d43cc703242a59f64b2103a1aaae345bb0e8fb771b3794","target":"graph","created_at":"2026-07-05T09:41:03Z","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/2411.07806/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fine-tuning large pre-trained foundation models (FMs) on distributed edge devices presents considerable computational and privacy challenges. Federated fine-tuning (FedFT) mitigates some privacy issues by facilitating collaborative model training without the need to share raw data. To lessen the computational burden on resource-limited devices, combining low-rank adaptation (LoRA) with federated learning enables parameter-efficient fine-tuning. Additionally, the split FedFT architecture partitions an FM between edge devices and a central server, reducing the necessity for complete model deploy","authors_text":"Hengtao He, Jun Zhang, Khaled B. Letaief, Shenghui Song, Tianqu Kang, Zixin Wang","cross_cats":["cs.CR","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-12T14:01:08Z","title":"Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.07806","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":"sha256:87890fdd48c9a8ab420e341773aa4e578c40bd1c53ea6d4c99b1466a82a544f9","target":"record","created_at":"2026-07-05T09:41:03Z","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":"9dbf254fecf19d632d346220a08f9694aa440fdac3b32f200bd79fd833176e7b","cross_cats_sorted":["cs.CR","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-12T14:01:08Z","title_canon_sha256":"ec9ace684a1e167c97bcda091676679ea385412cc0e5eec8b2b21040b82aa13a"},"schema_version":"1.0","source":{"id":"2411.07806","kind":"arxiv","version":2}},"canonical_sha256":"e66fb0e392712df49bf977d29b4b37d63575b7f471860c8d4ab7d426ff6694d0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e66fb0e392712df49bf977d29b4b37d63575b7f471860c8d4ab7d426ff6694d0","first_computed_at":"2026-07-05T09:41:03.479524Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:41:03.479524Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WSxGhbsULp8WoRQR+Yml/MPp/Bh2UQEAmB50tYXHfsOjspkauy3NuK3sZhMIgtq+gOAeJRMzbM5BQqEZcOOrCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:41:03.479973Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.07806","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:87890fdd48c9a8ab420e341773aa4e578c40bd1c53ea6d4c99b1466a82a544f9","sha256:d766df7f73cc698932d43cc703242a59f64b2103a1aaae345bb0e8fb771b3794"],"state_sha256":"572c0dcb8436c73664a5c6565b44b63b4d71d0a8eaaf346c2b669de3743763e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6D5riRIE4zcKG/G54amHS6wlOCdtka5lAaMElVlb0vBxkQL77uRWX4VUJXjKhKWM095APDNqzp2blQ6qdWWdDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T12:07:54.569629Z","bundle_sha256":"c19c5b7038180d8e6f0d756702d38eb33cd3de9b92618d09f5c19d3f685d01a8"}}