{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XETZE5LWRM3CYCON6FFTFUPSG6","short_pith_number":"pith:XETZE5LW","canonical_record":{"source":{"id":"2506.01396","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T07:44:17Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"1c4c2b9f2577219f01a83402169cadf82679c1fc06adbb3ad8e7e32c7b5590c6","abstract_canon_sha256":"eb54e643c47fcc38548f520948b8981ced23e39efb51486a484708145637f876"},"schema_version":"1.0"},"canonical_sha256":"b9279275768b362c09cdf14b32d1f237b117ed9e683b9ead51852132b416f2f5","source":{"kind":"arxiv","id":"2506.01396","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01396","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01396v2","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01396","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"pith_short_12","alias_value":"XETZE5LWRM3C","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"pith_short_16","alias_value":"XETZE5LWRM3CYCON","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"pith_short_8","alias_value":"XETZE5LW","created_at":"2026-06-11T01:09:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XETZE5LWRM3CYCON6FFTFUPSG6","target":"record","payload":{"canonical_record":{"source":{"id":"2506.01396","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T07:44:17Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"1c4c2b9f2577219f01a83402169cadf82679c1fc06adbb3ad8e7e32c7b5590c6","abstract_canon_sha256":"eb54e643c47fcc38548f520948b8981ced23e39efb51486a484708145637f876"},"schema_version":"1.0"},"canonical_sha256":"b9279275768b362c09cdf14b32d1f237b117ed9e683b9ead51852132b416f2f5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-11T01:09:13.629085Z","signature_b64":"xFVPLrkLAaVYD+1DIOaipUiPaNFCTjHXU6uvOcDVNrvedG1Qz+wgtcQDwXwNFoVk/f3uGu19zjNDGqsaj9O2DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9279275768b362c09cdf14b32d1f237b117ed9e683b9ead51852132b416f2f5","last_reissued_at":"2026-06-11T01:09:13.627978Z","signature_status":"signed_v1","first_computed_at":"2026-06-11T01:09:13.627978Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.01396","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":"2026-06-11T01:09:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W76NJSuZs+ymzUudbPGOfav8czaw+LWyBvIa3zkW7rPFUGuK7ljOqO0ZLOpeGmO5bi/wEJBr7C4IaQmSZfrWDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:30:32.835525Z"},"content_sha256":"bcf3350827617e367906a5aa5b84cd9d38d16de32d717c549ec9ac0a6d5ef06f","schema_version":"1.0","event_id":"sha256:bcf3350827617e367906a5aa5b84cd9d38d16de32d717c549ec9ac0a6d5ef06f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XETZE5LWRM3CYCON6FFTFUPSG6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Aki Rehn, Antti Honkela, Linzh Zhao, Mikko A. Heikkil\\\"a, Razane Tajeddine","submitted_at":"2025-06-02T07:44:17Z","abstract_excerpt":"Differential privacy (DP) has become an essential framework for privacy-preserving machine learning. Existing DP learning methods, however, often have disparate impacts on model predictions, e.g., for minority groups. Gradient clipping, which is often used in DP learning, can suppress larger gradients from challenging samples. We show that this problem is amplified by adaptive clipping, which will often shrink the clipping bound to tiny values to match a well-fitting majority, while significantly reducing the accuracy for others. We propose bounded adaptive clipping, which introduces a tunable"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01396","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/2506.01396/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":"2026-06-11T01:09:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"98yvfJ9wTjq82EauocmxByCLiJuMWs1+6wHWtMzoD7J2emUb6iEV+plLIwLwPD1Ih2BumvO9bVbBzRpS6F1VCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:30:32.836377Z"},"content_sha256":"70b4916d5ecf635310aca603b30f132e6c62a2a842d66bc8a91fe889334d3a6f","schema_version":"1.0","event_id":"sha256:70b4916d5ecf635310aca603b30f132e6c62a2a842d66bc8a91fe889334d3a6f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XETZE5LWRM3CYCON6FFTFUPSG6/bundle.json","state_url":"https://pith.science/pith/XETZE5LWRM3CYCON6FFTFUPSG6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XETZE5LWRM3CYCON6FFTFUPSG6/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":"2026-08-08T04:30:32Z","links":{"resolver":"https://pith.science/pith/XETZE5LWRM3CYCON6FFTFUPSG6","bundle":"https://pith.science/pith/XETZE5LWRM3CYCON6FFTFUPSG6/bundle.json","state":"https://pith.science/pith/XETZE5LWRM3CYCON6FFTFUPSG6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XETZE5LWRM3CYCON6FFTFUPSG6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XETZE5LWRM3CYCON6FFTFUPSG6","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":"eb54e643c47fcc38548f520948b8981ced23e39efb51486a484708145637f876","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T07:44:17Z","title_canon_sha256":"1c4c2b9f2577219f01a83402169cadf82679c1fc06adbb3ad8e7e32c7b5590c6"},"schema_version":"1.0","source":{"id":"2506.01396","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01396","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01396v2","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01396","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"pith_short_12","alias_value":"XETZE5LWRM3C","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"pith_short_16","alias_value":"XETZE5LWRM3CYCON","created_at":"2026-06-11T01:09:13Z"},{"alias_kind":"pith_short_8","alias_value":"XETZE5LW","created_at":"2026-06-11T01:09:13Z"}],"graph_snapshots":[{"event_id":"sha256:70b4916d5ecf635310aca603b30f132e6c62a2a842d66bc8a91fe889334d3a6f","target":"graph","created_at":"2026-06-11T01:09:13Z","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/2506.01396/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Differential privacy (DP) has become an essential framework for privacy-preserving machine learning. Existing DP learning methods, however, often have disparate impacts on model predictions, e.g., for minority groups. Gradient clipping, which is often used in DP learning, can suppress larger gradients from challenging samples. We show that this problem is amplified by adaptive clipping, which will often shrink the clipping bound to tiny values to match a well-fitting majority, while significantly reducing the accuracy for others. We propose bounded adaptive clipping, which introduces a tunable","authors_text":"Aki Rehn, Antti Honkela, Linzh Zhao, Mikko A. Heikkil\\\"a, Razane Tajeddine","cross_cats":["cs.CR","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T07:44:17Z","title":"Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01396","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:bcf3350827617e367906a5aa5b84cd9d38d16de32d717c549ec9ac0a6d5ef06f","target":"record","created_at":"2026-06-11T01:09:13Z","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":"eb54e643c47fcc38548f520948b8981ced23e39efb51486a484708145637f876","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T07:44:17Z","title_canon_sha256":"1c4c2b9f2577219f01a83402169cadf82679c1fc06adbb3ad8e7e32c7b5590c6"},"schema_version":"1.0","source":{"id":"2506.01396","kind":"arxiv","version":2}},"canonical_sha256":"b9279275768b362c09cdf14b32d1f237b117ed9e683b9ead51852132b416f2f5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9279275768b362c09cdf14b32d1f237b117ed9e683b9ead51852132b416f2f5","first_computed_at":"2026-06-11T01:09:13.627978Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-11T01:09:13.627978Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xFVPLrkLAaVYD+1DIOaipUiPaNFCTjHXU6uvOcDVNrvedG1Qz+wgtcQDwXwNFoVk/f3uGu19zjNDGqsaj9O2DQ==","signature_status":"signed_v1","signed_at":"2026-06-11T01:09:13.629085Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.01396","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bcf3350827617e367906a5aa5b84cd9d38d16de32d717c549ec9ac0a6d5ef06f","sha256:70b4916d5ecf635310aca603b30f132e6c62a2a842d66bc8a91fe889334d3a6f"],"state_sha256":"c4724876c6c4a5641e9d756df554968d420c40a20975b2ffb9695dc485a8c5a3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4k5uTHsFIGFa+pRC58a+j3vLPTxTa/LtU35GjJ6RduQ79RNuZrgpMG8d9nElapKCZLTEIXSSDgBULBIaXOPWBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T04:30:32.843114Z","bundle_sha256":"9af7c0100e52cce421463dfc96af58e26f7e412590358a029c899908d28d8c70"}}