{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DIYHBZJODXNLPVWARMINDVTBSG","short_pith_number":"pith:DIYHBZJO","canonical_record":{"source":{"id":"2405.17782","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T03:26:00Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"0d37dae385849ed1ae0f7752829278f3d2921de3cf1aa8fca25db0f1ba68dfc4","abstract_canon_sha256":"278504fcd35de59ca782735f2a1e0e43f48860fc8fffba686309bc9231026544"},"schema_version":"1.0"},"canonical_sha256":"1a3070e52e1ddab7d6c08b10d1d66191a1e549eac8dc0bf30dbb3f5766d24531","source":{"kind":"arxiv","id":"2405.17782","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.17782","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"arxiv_version","alias_value":"2405.17782v1","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.17782","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"pith_short_12","alias_value":"DIYHBZJODXNL","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"pith_short_16","alias_value":"DIYHBZJODXNLPVWA","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"pith_short_8","alias_value":"DIYHBZJO","created_at":"2026-07-05T08:24:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DIYHBZJODXNLPVWARMINDVTBSG","target":"record","payload":{"canonical_record":{"source":{"id":"2405.17782","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T03:26:00Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"0d37dae385849ed1ae0f7752829278f3d2921de3cf1aa8fca25db0f1ba68dfc4","abstract_canon_sha256":"278504fcd35de59ca782735f2a1e0e43f48860fc8fffba686309bc9231026544"},"schema_version":"1.0"},"canonical_sha256":"1a3070e52e1ddab7d6c08b10d1d66191a1e549eac8dc0bf30dbb3f5766d24531","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:24:11.380891Z","signature_b64":"FNJ/2ZFsnef+PxWDQn0sWxRDEjvNA7yktVp4ziyBEcUXKVufnP/oqpUTHE9D/uBpB7m9sfcVINDQbIof0qCuBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a3070e52e1ddab7d6c08b10d1d66191a1e549eac8dc0bf30dbb3f5766d24531","last_reissued_at":"2026-07-05T08:24:11.380427Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:24:11.380427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.17782","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":"2026-07-05T08:24:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yhHcl7Sp/xCNHTaOWh6lt/V8KWqrGbGra0SM4k9RYZBrMbnJVXhhUSoscEl8Hq7IX1AAvVC3MYycm+4xxgKjAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T18:32:51.645934Z"},"content_sha256":"94935f4717c8be4afce0dda834d6f17d8a01b761cd64105fb73a1baa6faab332","schema_version":"1.0","event_id":"sha256:94935f4717c8be4afce0dda834d6f17d8a01b761cd64105fb73a1baa6faab332"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DIYHBZJODXNLPVWARMINDVTBSG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processing","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.LG","authors_text":"Michael Lemmon, Nitesh Chawla, Yijun Tian, Yuying Duan","submitted_at":"2024-05-28T03:26:00Z","abstract_excerpt":"Federated Learning (FL) is a distributed machine learning framework in which a set of local communities collaboratively learn a shared global model while retaining all training data locally within each community. Two notions of fairness have recently emerged as important issues for federated learning: group fairness and community fairness. Group fairness requires that a model's decisions do not favor any particular group based on a set of legally protected attributes such as race or gender. Community fairness requires that global models exhibit similar levels of performance (accuracy) across a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.17782","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/2405.17782/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":"2026-07-05T08:24:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HgHncmv7rchkoqRCfPelRh7WkJLY0lKhicCQfzExHLaphzPNgSO46gC5PgnQTSQ1e9yOpd9hR+UFscr4bfgQBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T18:32:51.646545Z"},"content_sha256":"06e9ce8d4bd3300cbabdc0362ad4ab323391488f96aa6a15a1b3f9a88f065ded","schema_version":"1.0","event_id":"sha256:06e9ce8d4bd3300cbabdc0362ad4ab323391488f96aa6a15a1b3f9a88f065ded"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DIYHBZJODXNLPVWARMINDVTBSG/bundle.json","state_url":"https://pith.science/pith/DIYHBZJODXNLPVWARMINDVTBSG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DIYHBZJODXNLPVWARMINDVTBSG/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":"2026-08-11T18:32:51Z","links":{"resolver":"https://pith.science/pith/DIYHBZJODXNLPVWARMINDVTBSG","bundle":"https://pith.science/pith/DIYHBZJODXNLPVWARMINDVTBSG/bundle.json","state":"https://pith.science/pith/DIYHBZJODXNLPVWARMINDVTBSG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DIYHBZJODXNLPVWARMINDVTBSG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DIYHBZJODXNLPVWARMINDVTBSG","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":"278504fcd35de59ca782735f2a1e0e43f48860fc8fffba686309bc9231026544","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T03:26:00Z","title_canon_sha256":"0d37dae385849ed1ae0f7752829278f3d2921de3cf1aa8fca25db0f1ba68dfc4"},"schema_version":"1.0","source":{"id":"2405.17782","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.17782","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"arxiv_version","alias_value":"2405.17782v1","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.17782","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"pith_short_12","alias_value":"DIYHBZJODXNL","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"pith_short_16","alias_value":"DIYHBZJODXNLPVWA","created_at":"2026-07-05T08:24:11Z"},{"alias_kind":"pith_short_8","alias_value":"DIYHBZJO","created_at":"2026-07-05T08:24:11Z"}],"graph_snapshots":[{"event_id":"sha256:06e9ce8d4bd3300cbabdc0362ad4ab323391488f96aa6a15a1b3f9a88f065ded","target":"graph","created_at":"2026-07-05T08:24:11Z","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/2405.17782/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated Learning (FL) is a distributed machine learning framework in which a set of local communities collaboratively learn a shared global model while retaining all training data locally within each community. Two notions of fairness have recently emerged as important issues for federated learning: group fairness and community fairness. Group fairness requires that a model's decisions do not favor any particular group based on a set of legally protected attributes such as race or gender. Community fairness requires that global models exhibit similar levels of performance (accuracy) across a","authors_text":"Michael Lemmon, Nitesh Chawla, Yijun Tian, Yuying Duan","cross_cats":["cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T03:26:00Z","title":"Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.17782","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":"sha256:94935f4717c8be4afce0dda834d6f17d8a01b761cd64105fb73a1baa6faab332","target":"record","created_at":"2026-07-05T08:24:11Z","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":"278504fcd35de59ca782735f2a1e0e43f48860fc8fffba686309bc9231026544","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T03:26:00Z","title_canon_sha256":"0d37dae385849ed1ae0f7752829278f3d2921de3cf1aa8fca25db0f1ba68dfc4"},"schema_version":"1.0","source":{"id":"2405.17782","kind":"arxiv","version":1}},"canonical_sha256":"1a3070e52e1ddab7d6c08b10d1d66191a1e549eac8dc0bf30dbb3f5766d24531","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1a3070e52e1ddab7d6c08b10d1d66191a1e549eac8dc0bf30dbb3f5766d24531","first_computed_at":"2026-07-05T08:24:11.380427Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:24:11.380427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FNJ/2ZFsnef+PxWDQn0sWxRDEjvNA7yktVp4ziyBEcUXKVufnP/oqpUTHE9D/uBpB7m9sfcVINDQbIof0qCuBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:24:11.380891Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.17782","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:94935f4717c8be4afce0dda834d6f17d8a01b761cd64105fb73a1baa6faab332","sha256:06e9ce8d4bd3300cbabdc0362ad4ab323391488f96aa6a15a1b3f9a88f065ded"],"state_sha256":"24bc2ab9004ff735af68410e184ace292f534dc184c462f2dc4b0c26bc22c29e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bTDO9aOEW0SsLMT2Kw8gyYl9ox09BRCoAD9WxmWjxn6LELKX18SL1T8QZmYmIsnR6wMdmNiKHSRYfKmqCZm4CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T18:32:51.650461Z","bundle_sha256":"19ce2c33e84a6f628ca1182d0fce88c11b112376ec6c94879ee839d8b3a1b69b"}}