{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MGWMZKYXKG4JZWFGNCGWUTN5TV","short_pith_number":"pith:MGWMZKYX","canonical_record":{"source":{"id":"2403.02571","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-05T00:58:34Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bba823be8fd4dd7c13b31ee4e14cc181cb14f2d1307bd53aac2df1b854ebdd59","abstract_canon_sha256":"d467e7bcf76671ad8c957ce722eb68e67e3c10362e608a0ef36ec3083687a5ef"},"schema_version":"1.0"},"canonical_sha256":"61acccab1751b89cd8a6688d6a4dbd9d67d6b38f93363e597b752567688a77d9","source":{"kind":"arxiv","id":"2403.02571","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.02571","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"arxiv_version","alias_value":"2403.02571v1","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.02571","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"pith_short_12","alias_value":"MGWMZKYXKG4J","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"pith_short_16","alias_value":"MGWMZKYXKG4JZWFG","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"pith_short_8","alias_value":"MGWMZKYX","created_at":"2026-07-05T07:52:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MGWMZKYXKG4JZWFGNCGWUTN5TV","target":"record","payload":{"canonical_record":{"source":{"id":"2403.02571","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-05T00:58:34Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bba823be8fd4dd7c13b31ee4e14cc181cb14f2d1307bd53aac2df1b854ebdd59","abstract_canon_sha256":"d467e7bcf76671ad8c957ce722eb68e67e3c10362e608a0ef36ec3083687a5ef"},"schema_version":"1.0"},"canonical_sha256":"61acccab1751b89cd8a6688d6a4dbd9d67d6b38f93363e597b752567688a77d9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:52:19.203056Z","signature_b64":"bfmAj3vQfQ/abdCSf40Ahx8uT2QAkeQwjGNHHVEvAnZztz6eWfuZ5IPNQmLmMI+v0uVxDybogsTUL7Tz4++LAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61acccab1751b89cd8a6688d6a4dbd9d67d6b38f93363e597b752567688a77d9","last_reissued_at":"2026-07-05T07:52:19.202652Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:52:19.202652Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.02571","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":"2026-07-05T07:52:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v9JII4DSrwX7mOhwbIwV4cIDswt1LSNTOTs4do2X0eEEXJZgIKkO5U7Yl13mEf3XdkFsTnntq1acQQDNtg9gDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T06:32:17.666143Z"},"content_sha256":"13b21af9d4fcd393b6e5ada2e6ff0d773ba4d3499f377ffd43c58202468b972a","schema_version":"1.0","event_id":"sha256:13b21af9d4fcd393b6e5ada2e6ff0d773ba4d3499f377ffd43c58202468b972a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MGWMZKYXKG4JZWFGNCGWUTN5TV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Dongruo Zhou, Haixu Tang, John Mitchell, Rui Zhu, Xiaofeng Wang, Zhikun Zhang, Zihao Wang","submitted_at":"2024-03-05T00:58:34Z","abstract_excerpt":"Recent developments have underscored the critical role of \\textit{differential privacy} (DP) in safeguarding individual data for training machine learning models. However, integrating DP oftentimes incurs significant model performance degradation due to the perturbation introduced into the training process, presenting a formidable challenge in the {differentially private machine learning} (DPML) field. To this end, several mitigative efforts have been proposed, typically revolving around formulating new DPML algorithms or relaxing DP definitions to harmonize with distinct contexts. In spite of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.02571","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/2403.02571/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":"2026-07-05T07:52:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M4Eecr6jmL+1PAO237jlzWpGc41t1t7wOVp+MpeMxFynYSWX6WdaH8hZ4Z1QbXbujlHBN/Wtyt2Y3iVNPSevBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T06:32:17.666655Z"},"content_sha256":"ae36ef1d9c548331b1bbd5a052b2011e841610a016fad2a725b6cb4c77a8e02d","schema_version":"1.0","event_id":"sha256:ae36ef1d9c548331b1bbd5a052b2011e841610a016fad2a725b6cb4c77a8e02d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MGWMZKYXKG4JZWFGNCGWUTN5TV/bundle.json","state_url":"https://pith.science/pith/MGWMZKYXKG4JZWFGNCGWUTN5TV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MGWMZKYXKG4JZWFGNCGWUTN5TV/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":"2026-08-10T06:32:17Z","links":{"resolver":"https://pith.science/pith/MGWMZKYXKG4JZWFGNCGWUTN5TV","bundle":"https://pith.science/pith/MGWMZKYXKG4JZWFGNCGWUTN5TV/bundle.json","state":"https://pith.science/pith/MGWMZKYXKG4JZWFGNCGWUTN5TV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MGWMZKYXKG4JZWFGNCGWUTN5TV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MGWMZKYXKG4JZWFGNCGWUTN5TV","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":"d467e7bcf76671ad8c957ce722eb68e67e3c10362e608a0ef36ec3083687a5ef","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-05T00:58:34Z","title_canon_sha256":"bba823be8fd4dd7c13b31ee4e14cc181cb14f2d1307bd53aac2df1b854ebdd59"},"schema_version":"1.0","source":{"id":"2403.02571","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.02571","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"arxiv_version","alias_value":"2403.02571v1","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.02571","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"pith_short_12","alias_value":"MGWMZKYXKG4J","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"pith_short_16","alias_value":"MGWMZKYXKG4JZWFG","created_at":"2026-07-05T07:52:19Z"},{"alias_kind":"pith_short_8","alias_value":"MGWMZKYX","created_at":"2026-07-05T07:52:19Z"}],"graph_snapshots":[{"event_id":"sha256:ae36ef1d9c548331b1bbd5a052b2011e841610a016fad2a725b6cb4c77a8e02d","target":"graph","created_at":"2026-07-05T07:52:19Z","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/2403.02571/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent developments have underscored the critical role of \\textit{differential privacy} (DP) in safeguarding individual data for training machine learning models. However, integrating DP oftentimes incurs significant model performance degradation due to the perturbation introduced into the training process, presenting a formidable challenge in the {differentially private machine learning} (DPML) field. To this end, several mitigative efforts have been proposed, typically revolving around formulating new DPML algorithms or relaxing DP definitions to harmonize with distinct contexts. In spite of","authors_text":"Dongruo Zhou, Haixu Tang, John Mitchell, Rui Zhu, Xiaofeng Wang, Zhikun Zhang, Zihao Wang","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-05T00:58:34Z","title":"DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.02571","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":"sha256:13b21af9d4fcd393b6e5ada2e6ff0d773ba4d3499f377ffd43c58202468b972a","target":"record","created_at":"2026-07-05T07:52:19Z","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":"d467e7bcf76671ad8c957ce722eb68e67e3c10362e608a0ef36ec3083687a5ef","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-05T00:58:34Z","title_canon_sha256":"bba823be8fd4dd7c13b31ee4e14cc181cb14f2d1307bd53aac2df1b854ebdd59"},"schema_version":"1.0","source":{"id":"2403.02571","kind":"arxiv","version":1}},"canonical_sha256":"61acccab1751b89cd8a6688d6a4dbd9d67d6b38f93363e597b752567688a77d9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"61acccab1751b89cd8a6688d6a4dbd9d67d6b38f93363e597b752567688a77d9","first_computed_at":"2026-07-05T07:52:19.202652Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:52:19.202652Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bfmAj3vQfQ/abdCSf40Ahx8uT2QAkeQwjGNHHVEvAnZztz6eWfuZ5IPNQmLmMI+v0uVxDybogsTUL7Tz4++LAw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:52:19.203056Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.02571","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:13b21af9d4fcd393b6e5ada2e6ff0d773ba4d3499f377ffd43c58202468b972a","sha256:ae36ef1d9c548331b1bbd5a052b2011e841610a016fad2a725b6cb4c77a8e02d"],"state_sha256":"d716d70e7bc12fc54241eacfae6d4d89589f64a531462c2dc2265882855da272"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pg9dTH5f9ovoYW4Ds+uU6+vTYdJe8+/BrWs6Hg9RgrxFVmVLXImnF9JEpfiLF068+Y8ad4oC5Du9HgP9qTCpBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T06:32:17.672198Z","bundle_sha256":"eecc800363b9132e793d1f91923e01a550ea5975abac78ebe81b8e5f41c699db"}}