{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:OP5R73XMSH36JVWS5CQHNNJCVW","short_pith_number":"pith:OP5R73XM","canonical_record":{"source":{"id":"2505.06651","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T13:57:57Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"542d96beee11e4480ecbd3e9bb6b4f706f43d8e51d5185d31f28ca5aae40402a","abstract_canon_sha256":"4231d38218bd7712570f93813453504cb0e4cfb1232073dac02c4b9c6df5ad1e"},"schema_version":"1.0"},"canonical_sha256":"73fb1feeec91f7e4d6d2e8a076b522ad8bc6396e95c69303997c0fcf40f86a73","source":{"kind":"arxiv","id":"2505.06651","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.06651","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"arxiv_version","alias_value":"2505.06651v1","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.06651","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"pith_short_12","alias_value":"OP5R73XMSH36","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"pith_short_16","alias_value":"OP5R73XMSH36JVWS","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"pith_short_8","alias_value":"OP5R73XM","created_at":"2026-07-05T11:01:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:OP5R73XMSH36JVWS5CQHNNJCVW","target":"record","payload":{"canonical_record":{"source":{"id":"2505.06651","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T13:57:57Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"542d96beee11e4480ecbd3e9bb6b4f706f43d8e51d5185d31f28ca5aae40402a","abstract_canon_sha256":"4231d38218bd7712570f93813453504cb0e4cfb1232073dac02c4b9c6df5ad1e"},"schema_version":"1.0"},"canonical_sha256":"73fb1feeec91f7e4d6d2e8a076b522ad8bc6396e95c69303997c0fcf40f86a73","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:01:13.714778Z","signature_b64":"i5RaHqJcf6qqd4cdwfMoKuSbWMopeL/LoPqCz00jyIpLnbr5QVkDBRivDLZEuGJdXcoI0KU6w/lH0HD4v/tOAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73fb1feeec91f7e4d6d2e8a076b522ad8bc6396e95c69303997c0fcf40f86a73","last_reissued_at":"2026-07-05T11:01:13.714106Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:01:13.714106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.06651","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":"2026-07-05T11:01:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gM8/D4OQRlACZ7a6y20LTO7Ulh0ooqRVEXkJPAOyswGfRLaI1iW2V5ze/ReT6pEzEDqNHLMpr8T53sBTr18vDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T14:49:52.298058Z"},"content_sha256":"3499d88ce560c08e49eebbf954f1cbe471da7d4fe9f07ecac98aa9def136f68a","schema_version":"1.0","event_id":"sha256:3499d88ce560c08e49eebbf954f1cbe471da7d4fe9f07ecac98aa9def136f68a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:OP5R73XMSH36JVWS5CQHNNJCVW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dyn-D$^2$P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jinming Xu, Shouling Ji, Xin Wang, Yan Huang, Zehan Zhu","submitted_at":"2025-05-10T13:57:57Z","abstract_excerpt":"Most existing decentralized learning methods with differential privacy (DP) guarantee rely on constant gradient clipping bounds and fixed-level DP Gaussian noises for each node throughout the training process, leading to a significant accuracy degradation compared to non-private counterparts. In this paper, we propose a new Dynamic Differentially Private Decentralized learning approach (termed Dyn-D$^2$P) tailored for general time-varying directed networks. Leveraging the Gaussian DP (GDP) framework for privacy accounting, Dyn-D$^2$P dynamically adjusts gradient clipping bounds and noise level"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.06651","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/2505.06651/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":"2026-07-05T11:01:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dDGR08yPEblarkg9/bth7rBoCxdW4D3FaAF3o2kEF217xNX+Z4rNyzOA/huTGrjpawynVmEVWkRkUxpPZdBNAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T14:49:52.298568Z"},"content_sha256":"4bc8f317e6af4cf802f772168e8c0a4adfc64fa9b7d6cabba1520ba4b63f87bc","schema_version":"1.0","event_id":"sha256:4bc8f317e6af4cf802f772168e8c0a4adfc64fa9b7d6cabba1520ba4b63f87bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OP5R73XMSH36JVWS5CQHNNJCVW/bundle.json","state_url":"https://pith.science/pith/OP5R73XMSH36JVWS5CQHNNJCVW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OP5R73XMSH36JVWS5CQHNNJCVW/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":"2026-08-16T14:49:52Z","links":{"resolver":"https://pith.science/pith/OP5R73XMSH36JVWS5CQHNNJCVW","bundle":"https://pith.science/pith/OP5R73XMSH36JVWS5CQHNNJCVW/bundle.json","state":"https://pith.science/pith/OP5R73XMSH36JVWS5CQHNNJCVW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OP5R73XMSH36JVWS5CQHNNJCVW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:OP5R73XMSH36JVWS5CQHNNJCVW","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":"4231d38218bd7712570f93813453504cb0e4cfb1232073dac02c4b9c6df5ad1e","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T13:57:57Z","title_canon_sha256":"542d96beee11e4480ecbd3e9bb6b4f706f43d8e51d5185d31f28ca5aae40402a"},"schema_version":"1.0","source":{"id":"2505.06651","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.06651","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"arxiv_version","alias_value":"2505.06651v1","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.06651","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"pith_short_12","alias_value":"OP5R73XMSH36","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"pith_short_16","alias_value":"OP5R73XMSH36JVWS","created_at":"2026-07-05T11:01:13Z"},{"alias_kind":"pith_short_8","alias_value":"OP5R73XM","created_at":"2026-07-05T11:01:13Z"}],"graph_snapshots":[{"event_id":"sha256:4bc8f317e6af4cf802f772168e8c0a4adfc64fa9b7d6cabba1520ba4b63f87bc","target":"graph","created_at":"2026-07-05T11:01:13Z","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/2505.06651/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most existing decentralized learning methods with differential privacy (DP) guarantee rely on constant gradient clipping bounds and fixed-level DP Gaussian noises for each node throughout the training process, leading to a significant accuracy degradation compared to non-private counterparts. In this paper, we propose a new Dynamic Differentially Private Decentralized learning approach (termed Dyn-D$^2$P) tailored for general time-varying directed networks. Leveraging the Gaussian DP (GDP) framework for privacy accounting, Dyn-D$^2$P dynamically adjusts gradient clipping bounds and noise level","authors_text":"Jinming Xu, Shouling Ji, Xin Wang, Yan Huang, Zehan Zhu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T13:57:57Z","title":"Dyn-D$^2$P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.06651","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":"sha256:3499d88ce560c08e49eebbf954f1cbe471da7d4fe9f07ecac98aa9def136f68a","target":"record","created_at":"2026-07-05T11:01:13Z","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":"4231d38218bd7712570f93813453504cb0e4cfb1232073dac02c4b9c6df5ad1e","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T13:57:57Z","title_canon_sha256":"542d96beee11e4480ecbd3e9bb6b4f706f43d8e51d5185d31f28ca5aae40402a"},"schema_version":"1.0","source":{"id":"2505.06651","kind":"arxiv","version":1}},"canonical_sha256":"73fb1feeec91f7e4d6d2e8a076b522ad8bc6396e95c69303997c0fcf40f86a73","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"73fb1feeec91f7e4d6d2e8a076b522ad8bc6396e95c69303997c0fcf40f86a73","first_computed_at":"2026-07-05T11:01:13.714106Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:01:13.714106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"i5RaHqJcf6qqd4cdwfMoKuSbWMopeL/LoPqCz00jyIpLnbr5QVkDBRivDLZEuGJdXcoI0KU6w/lH0HD4v/tOAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:01:13.714778Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.06651","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3499d88ce560c08e49eebbf954f1cbe471da7d4fe9f07ecac98aa9def136f68a","sha256:4bc8f317e6af4cf802f772168e8c0a4adfc64fa9b7d6cabba1520ba4b63f87bc"],"state_sha256":"e024a29b60bf9becd3cbe0328189e9f135fb76c0879f0e9317c842aba8cea7b1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kf1qr9A9Fmxxq6qEWESmq7iXVO0VKXc5sbtH3wg/w8Qdv1GJq3+Jk/aHOxt5HxaWgA7ciowPxIzvsgWK3TbJBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T14:49:52.302934Z","bundle_sha256":"1401f0fdabd03b6b273949940caf781be38f742e8e82b9e22c440cd407ab11aa"}}