{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XHPD5ENMTDQINJFS24LKWEEUUL","short_pith_number":"pith:XHPD5ENM","canonical_record":{"source":{"id":"2407.14710","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-20T00:11:59Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"87dfd1b4c78efdd7263440598564497c5fb4edb4d91e88ffdffe749a24c3e1ed","abstract_canon_sha256":"f2d0498f24ad91e5ff68aa3f7ff48e0acd28250ea6f00cb30028a919460b3cbe"},"schema_version":"1.0"},"canonical_sha256":"b9de3e91ac98e086a4b2d716ab1094a2dc6e8c5541f146a17fd69c943cf844c2","source":{"kind":"arxiv","id":"2407.14710","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.14710","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"arxiv_version","alias_value":"2407.14710v2","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.14710","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"pith_short_12","alias_value":"XHPD5ENMTDQI","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"pith_short_16","alias_value":"XHPD5ENMTDQINJFS","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"pith_short_8","alias_value":"XHPD5ENM","created_at":"2026-07-05T08:47:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XHPD5ENMTDQINJFS24LKWEEUUL","target":"record","payload":{"canonical_record":{"source":{"id":"2407.14710","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-20T00:11:59Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"87dfd1b4c78efdd7263440598564497c5fb4edb4d91e88ffdffe749a24c3e1ed","abstract_canon_sha256":"f2d0498f24ad91e5ff68aa3f7ff48e0acd28250ea6f00cb30028a919460b3cbe"},"schema_version":"1.0"},"canonical_sha256":"b9de3e91ac98e086a4b2d716ab1094a2dc6e8c5541f146a17fd69c943cf844c2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:47:55.108683Z","signature_b64":"j/uYmum8u6Vvz//LzMiBpDGGNPTgj5m0wOZTAsTVFEqj5WpNpUjkgSVFJW4bYJM1fP+9rlb7ol+0sD+O18G0Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9de3e91ac98e086a4b2d716ab1094a2dc6e8c5541f146a17fd69c943cf844c2","last_reissued_at":"2026-07-05T08:47:55.108233Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:47:55.108233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.14710","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":"2026-07-05T08:47:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1SBJngI2Q7DwnZ4/xOo2omrsOVVJbp5tRlAgd42v/lxueNnZ95513HJBheQAP3KJ50c16qepZOajZ3VbDYzZBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T02:33:17.274572Z"},"content_sha256":"8b5c6bacec23b273ef682a4199e10e87ac0161a72a9918d641039090ac8f8702","schema_version":"1.0","event_id":"sha256:8b5c6bacec23b273ef682a4199e10e87ac0161a72a9918d641039090ac8f8702"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XHPD5ENMTDQINJFS24LKWEEUUL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Ashish Kundu, Binghui Wang, Hanbin Hong, Meisam Mohammady, Shenao Yan, Shuya Feng, Yuan Hong","submitted_at":"2024-07-20T00:11:59Z","abstract_excerpt":"Differentially private federated learning (DP-FL) is a promising technique for collaborative model training while ensuring provable privacy for clients. However, optimizing the tradeoff between privacy and accuracy remains a critical challenge. To our best knowledge, we propose the first DP-FL framework (namely UDP-FL), which universally harmonizes any randomization mechanism (e.g., an optimal one) with the Gaussian Moments Accountant (viz. DP-SGD) to significantly boost accuracy and convergence. Specifically, UDP-FL demonstrates enhanced model performance by mitigating the reliance on Gaussia"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.14710","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/2407.14710/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":"2026-07-05T08:47:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q+7NtbVsy3AkhjSwE/gmqnMBizm7n2jmyfe6KBJrFThZKur4yTojSAcA8qi/cNX/YdxMdcFuooWquE7c+uaUAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T02:33:17.275517Z"},"content_sha256":"da40d76971aafcfc886f4f72719619e815058e91072ecfecf458cc66dd9679c8","schema_version":"1.0","event_id":"sha256:da40d76971aafcfc886f4f72719619e815058e91072ecfecf458cc66dd9679c8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XHPD5ENMTDQINJFS24LKWEEUUL/bundle.json","state_url":"https://pith.science/pith/XHPD5ENMTDQINJFS24LKWEEUUL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XHPD5ENMTDQINJFS24LKWEEUUL/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":"2026-08-13T02:33:17Z","links":{"resolver":"https://pith.science/pith/XHPD5ENMTDQINJFS24LKWEEUUL","bundle":"https://pith.science/pith/XHPD5ENMTDQINJFS24LKWEEUUL/bundle.json","state":"https://pith.science/pith/XHPD5ENMTDQINJFS24LKWEEUUL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XHPD5ENMTDQINJFS24LKWEEUUL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XHPD5ENMTDQINJFS24LKWEEUUL","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":"f2d0498f24ad91e5ff68aa3f7ff48e0acd28250ea6f00cb30028a919460b3cbe","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-20T00:11:59Z","title_canon_sha256":"87dfd1b4c78efdd7263440598564497c5fb4edb4d91e88ffdffe749a24c3e1ed"},"schema_version":"1.0","source":{"id":"2407.14710","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.14710","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"arxiv_version","alias_value":"2407.14710v2","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.14710","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"pith_short_12","alias_value":"XHPD5ENMTDQI","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"pith_short_16","alias_value":"XHPD5ENMTDQINJFS","created_at":"2026-07-05T08:47:55Z"},{"alias_kind":"pith_short_8","alias_value":"XHPD5ENM","created_at":"2026-07-05T08:47:55Z"}],"graph_snapshots":[{"event_id":"sha256:da40d76971aafcfc886f4f72719619e815058e91072ecfecf458cc66dd9679c8","target":"graph","created_at":"2026-07-05T08:47:55Z","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/2407.14710/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Differentially private federated learning (DP-FL) is a promising technique for collaborative model training while ensuring provable privacy for clients. However, optimizing the tradeoff between privacy and accuracy remains a critical challenge. To our best knowledge, we propose the first DP-FL framework (namely UDP-FL), which universally harmonizes any randomization mechanism (e.g., an optimal one) with the Gaussian Moments Accountant (viz. DP-SGD) to significantly boost accuracy and convergence. Specifically, UDP-FL demonstrates enhanced model performance by mitigating the reliance on Gaussia","authors_text":"Ashish Kundu, Binghui Wang, Hanbin Hong, Meisam Mohammady, Shenao Yan, Shuya Feng, Yuan Hong","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-20T00:11:59Z","title":"Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.14710","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":"sha256:8b5c6bacec23b273ef682a4199e10e87ac0161a72a9918d641039090ac8f8702","target":"record","created_at":"2026-07-05T08:47:55Z","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":"f2d0498f24ad91e5ff68aa3f7ff48e0acd28250ea6f00cb30028a919460b3cbe","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-20T00:11:59Z","title_canon_sha256":"87dfd1b4c78efdd7263440598564497c5fb4edb4d91e88ffdffe749a24c3e1ed"},"schema_version":"1.0","source":{"id":"2407.14710","kind":"arxiv","version":2}},"canonical_sha256":"b9de3e91ac98e086a4b2d716ab1094a2dc6e8c5541f146a17fd69c943cf844c2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9de3e91ac98e086a4b2d716ab1094a2dc6e8c5541f146a17fd69c943cf844c2","first_computed_at":"2026-07-05T08:47:55.108233Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:47:55.108233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"j/uYmum8u6Vvz//LzMiBpDGGNPTgj5m0wOZTAsTVFEqj5WpNpUjkgSVFJW4bYJM1fP+9rlb7ol+0sD+O18G0Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:47:55.108683Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.14710","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8b5c6bacec23b273ef682a4199e10e87ac0161a72a9918d641039090ac8f8702","sha256:da40d76971aafcfc886f4f72719619e815058e91072ecfecf458cc66dd9679c8"],"state_sha256":"817d25e48d71a606dc3e79f608e674203799e49551abd4384c836afb9cd8c866"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OQuhXtOyr/mVjb0qSwJnlbKcn4Qg8q9p3KCRwOLXXr+5IS9rRX5Ba3ryT+74gvtQxTk1YxE9xaqqWRllBmksBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T02:33:17.281941Z","bundle_sha256":"b50d714c054beeacf063a666b5984a1fa66b05e8253a92185fd8ef8baed1dfef"}}