{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:E3ZQRQY6TAQGPKFMXW3TRATLXE","short_pith_number":"pith:E3ZQRQY6","canonical_record":{"source":{"id":"2408.16003","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-13T14:03:10Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"03fd4e2e8fd57fc7989b5acb13985aff78576b4c53c6ad48bd2b2bafb405f36a","abstract_canon_sha256":"f2c30699f59ce20f2a3172ab1cc27b3c496048b7a0039675f42587b7d097753e"},"schema_version":"1.0"},"canonical_sha256":"26f308c31e982067a8acbdb738826bb92759bc349fa3e84563bbd061da3e713f","source":{"kind":"arxiv","id":"2408.16003","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.16003","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"arxiv_version","alias_value":"2408.16003v1","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.16003","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"pith_short_12","alias_value":"E3ZQRQY6TAQG","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"pith_short_16","alias_value":"E3ZQRQY6TAQGPKFM","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"pith_short_8","alias_value":"E3ZQRQY6","created_at":"2026-07-05T09:00:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:E3ZQRQY6TAQGPKFMXW3TRATLXE","target":"record","payload":{"canonical_record":{"source":{"id":"2408.16003","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-13T14:03:10Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"03fd4e2e8fd57fc7989b5acb13985aff78576b4c53c6ad48bd2b2bafb405f36a","abstract_canon_sha256":"f2c30699f59ce20f2a3172ab1cc27b3c496048b7a0039675f42587b7d097753e"},"schema_version":"1.0"},"canonical_sha256":"26f308c31e982067a8acbdb738826bb92759bc349fa3e84563bbd061da3e713f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:00:24.633701Z","signature_b64":"nlHYeCP+BzWdNpO9X0y+WEcP8v0vO93W5V/mZk8QIxpFkdTkIXQOj3ViRd1PqS8UPGCWu+T75gkQYlPRmXM4CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"26f308c31e982067a8acbdb738826bb92759bc349fa3e84563bbd061da3e713f","last_reissued_at":"2026-07-05T09:00:24.633281Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:00:24.633281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.16003","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":"2026-07-05T09:00:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8GJUxmmx67wMPn0GrkMOQnZz0TQ+oRj1QzWMWlFz6wbvppmJ5XY03yFcr98LNEAKIaOI/iVwFhQpTYAkJ6ifBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T16:54:31.279083Z"},"content_sha256":"6cf58ace543fbc526d0b6e7dd31c525b437839e9899d86d742fd39fa9c42fa32","schema_version":"1.0","event_id":"sha256:6cf58ace543fbc526d0b6e7dd31c525b437839e9899d86d742fd39fa9c42fa32"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:E3ZQRQY6TAQGPKFMXW3TRATLXE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Meta-Learning for Federated Face Recognition in Imbalanced Data Regimes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.CV","authors_text":"Arwin Gansekoele, Emiel Hess, Sandjai Bhulai","submitted_at":"2024-08-13T14:03:10Z","abstract_excerpt":"The growing privacy concerns surrounding face image data demand new techniques that can guarantee user privacy. One such face recognition technique that claims to achieve better user privacy is Federated Face Recognition (FRR), a subfield of Federated Learning (FL). However, FFR faces challenges due to the heterogeneity of the data, given the large number of classes that need to be handled. To overcome this problem, solutions are sought in the field of personalized FL. This work introduces three new data partitions based on the CelebA dataset, each with a different form of data heterogeneity. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.16003","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/2408.16003/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":"2026-07-05T09:00:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0rFW/J9Xp0naNVHcvf4D39Z5u36npgwoMxvE9IMuFtOsKlIZE+RVgbgp+hKgPlAPzYPqM26KY0OZQbX2uP/6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T16:54:31.279935Z"},"content_sha256":"c1fdc52b2b6ef19d39aafd34127074ac7ae4bdd9bfce2675f50a4bb717ecc5ac","schema_version":"1.0","event_id":"sha256:c1fdc52b2b6ef19d39aafd34127074ac7ae4bdd9bfce2675f50a4bb717ecc5ac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E3ZQRQY6TAQGPKFMXW3TRATLXE/bundle.json","state_url":"https://pith.science/pith/E3ZQRQY6TAQGPKFMXW3TRATLXE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E3ZQRQY6TAQGPKFMXW3TRATLXE/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":"2026-08-22T16:54:31Z","links":{"resolver":"https://pith.science/pith/E3ZQRQY6TAQGPKFMXW3TRATLXE","bundle":"https://pith.science/pith/E3ZQRQY6TAQGPKFMXW3TRATLXE/bundle.json","state":"https://pith.science/pith/E3ZQRQY6TAQGPKFMXW3TRATLXE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E3ZQRQY6TAQGPKFMXW3TRATLXE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:E3ZQRQY6TAQGPKFMXW3TRATLXE","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":"f2c30699f59ce20f2a3172ab1cc27b3c496048b7a0039675f42587b7d097753e","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-13T14:03:10Z","title_canon_sha256":"03fd4e2e8fd57fc7989b5acb13985aff78576b4c53c6ad48bd2b2bafb405f36a"},"schema_version":"1.0","source":{"id":"2408.16003","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.16003","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"arxiv_version","alias_value":"2408.16003v1","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.16003","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"pith_short_12","alias_value":"E3ZQRQY6TAQG","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"pith_short_16","alias_value":"E3ZQRQY6TAQGPKFM","created_at":"2026-07-05T09:00:24Z"},{"alias_kind":"pith_short_8","alias_value":"E3ZQRQY6","created_at":"2026-07-05T09:00:24Z"}],"graph_snapshots":[{"event_id":"sha256:c1fdc52b2b6ef19d39aafd34127074ac7ae4bdd9bfce2675f50a4bb717ecc5ac","target":"graph","created_at":"2026-07-05T09:00:24Z","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/2408.16003/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The growing privacy concerns surrounding face image data demand new techniques that can guarantee user privacy. One such face recognition technique that claims to achieve better user privacy is Federated Face Recognition (FRR), a subfield of Federated Learning (FL). However, FFR faces challenges due to the heterogeneity of the data, given the large number of classes that need to be handled. To overcome this problem, solutions are sought in the field of personalized FL. This work introduces three new data partitions based on the CelebA dataset, each with a different form of data heterogeneity. ","authors_text":"Arwin Gansekoele, Emiel Hess, Sandjai Bhulai","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-13T14:03:10Z","title":"Meta-Learning for Federated Face Recognition in Imbalanced Data Regimes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.16003","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":"sha256:6cf58ace543fbc526d0b6e7dd31c525b437839e9899d86d742fd39fa9c42fa32","target":"record","created_at":"2026-07-05T09:00:24Z","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":"f2c30699f59ce20f2a3172ab1cc27b3c496048b7a0039675f42587b7d097753e","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-13T14:03:10Z","title_canon_sha256":"03fd4e2e8fd57fc7989b5acb13985aff78576b4c53c6ad48bd2b2bafb405f36a"},"schema_version":"1.0","source":{"id":"2408.16003","kind":"arxiv","version":1}},"canonical_sha256":"26f308c31e982067a8acbdb738826bb92759bc349fa3e84563bbd061da3e713f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"26f308c31e982067a8acbdb738826bb92759bc349fa3e84563bbd061da3e713f","first_computed_at":"2026-07-05T09:00:24.633281Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:00:24.633281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nlHYeCP+BzWdNpO9X0y+WEcP8v0vO93W5V/mZk8QIxpFkdTkIXQOj3ViRd1PqS8UPGCWu+T75gkQYlPRmXM4CA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:00:24.633701Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.16003","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6cf58ace543fbc526d0b6e7dd31c525b437839e9899d86d742fd39fa9c42fa32","sha256:c1fdc52b2b6ef19d39aafd34127074ac7ae4bdd9bfce2675f50a4bb717ecc5ac"],"state_sha256":"7345038f0d864ef51e70c517175e4ed2a5a37b0faed5c023663e890ef31b8aea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jIDRHvwxd/Q393t8M834Ic3Le3BZlHjBN660pS4QMBWmqczMxmORhRjlyeK9PTrEEVH7vr61ANbzLCMZ3uNICg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T16:54:31.283546Z","bundle_sha256":"08ab5258c3b89042c0f8ec21479a0724022da7bd15c3fe8b7cf288f968587809"}}