{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QPN4ZJ6SXHH3UDCXWEARHRYK42","short_pith_number":"pith:QPN4ZJ6S","canonical_record":{"source":{"id":"2404.06430","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T16:23:01Z","cross_cats_sorted":["cs.AI","cs.CR","cs.CV"],"title_canon_sha256":"c7272c30b4427d40d1e9d5c0b473ac870203536efa3d11cfdf962b184b32cf27","abstract_canon_sha256":"0100edf94b6f59b44fcda413d3bd4425f91617e845043ede8b43bd25e23a38e3"},"schema_version":"1.0"},"canonical_sha256":"83dbcca7d2b9cfba0c57b10113c70ae6876b09513fa95d27fdff825d7765c1ed","source":{"kind":"arxiv","id":"2404.06430","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.06430","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"arxiv_version","alias_value":"2404.06430v2","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.06430","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"pith_short_12","alias_value":"QPN4ZJ6SXHH3","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"pith_short_16","alias_value":"QPN4ZJ6SXHH3UDCX","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"pith_short_8","alias_value":"QPN4ZJ6S","created_at":"2026-07-05T09:46:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QPN4ZJ6SXHH3UDCXWEARHRYK42","target":"record","payload":{"canonical_record":{"source":{"id":"2404.06430","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T16:23:01Z","cross_cats_sorted":["cs.AI","cs.CR","cs.CV"],"title_canon_sha256":"c7272c30b4427d40d1e9d5c0b473ac870203536efa3d11cfdf962b184b32cf27","abstract_canon_sha256":"0100edf94b6f59b44fcda413d3bd4425f91617e845043ede8b43bd25e23a38e3"},"schema_version":"1.0"},"canonical_sha256":"83dbcca7d2b9cfba0c57b10113c70ae6876b09513fa95d27fdff825d7765c1ed","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:46:46.167801Z","signature_b64":"u3pWpheYUEXpMbxAy/x8Hlfz7RZ7SmmZf4Jyjd9H4cNHBxSFIdvHyRwmK39VGrUsMsO6S7HG+ni970YiB0RfBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83dbcca7d2b9cfba0c57b10113c70ae6876b09513fa95d27fdff825d7765c1ed","last_reissued_at":"2026-07-05T09:46:46.167268Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:46:46.167268Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.06430","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":"2026-07-05T09:46:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nGnrOrm5uHuNkjQSAAd8yIAYuibagOduKaBQ9u0hXVbcwk4KbFlxJCNcreBLhi5Ipot3LV1kRs+6n1eG7vq2Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T04:18:03.013666Z"},"content_sha256":"5e4099429b6341854bd502a6cbb21baad0ef07d0c388ac3a4a3cbcbc611b4191","schema_version":"1.0","event_id":"sha256:5e4099429b6341854bd502a6cbb21baad0ef07d0c388ac3a4a3cbcbc611b4191"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QPN4ZJ6SXHH3UDCXWEARHRYK42","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"pfl-research: simulation framework for accelerating research in Private Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR","cs.CV"],"primary_cat":"cs.LG","authors_text":"\\'Aine Cahill, Congzheng Song, Filip Granqvist, Martin Pelikan, Mona Chitnis, Natarajan Krishnaswami, Rogier Van Dalen, Vojta Jina, Xiaojun Feng, Yi Sheng Chan","submitted_at":"2024-04-09T16:23:01Z","abstract_excerpt":"Federated learning (FL) is an emerging machine learning (ML) training paradigm where clients own their data and collaborate to train a global model, without revealing any data to the server and other participants. Researchers commonly perform experiments in a simulation environment to quickly iterate on ideas. However, existing open-source tools do not offer the efficiency required to simulate FL on larger and more realistic FL datasets. We introduce pfl-research, a fast, modular, and easy-to-use Python framework for simulating FL. It supports TensorFlow, PyTorch, and non-neural network models"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.06430","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/2404.06430/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":"2026-07-05T09:46:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RHz3/W3DlolPjn4U/elN8aau8xxr35IAMKOi7QTwUPLzeWMTAAPtA+Hin5HT6TiZBKhRZm757WfsJpjB8sv8BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T04:18:03.014185Z"},"content_sha256":"e12a3be73d5adbe84b49f0cd52e8353090a8f735681d626f9e4e28c37e534b71","schema_version":"1.0","event_id":"sha256:e12a3be73d5adbe84b49f0cd52e8353090a8f735681d626f9e4e28c37e534b71"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QPN4ZJ6SXHH3UDCXWEARHRYK42/bundle.json","state_url":"https://pith.science/pith/QPN4ZJ6SXHH3UDCXWEARHRYK42/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QPN4ZJ6SXHH3UDCXWEARHRYK42/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":"2026-08-16T04:18:03Z","links":{"resolver":"https://pith.science/pith/QPN4ZJ6SXHH3UDCXWEARHRYK42","bundle":"https://pith.science/pith/QPN4ZJ6SXHH3UDCXWEARHRYK42/bundle.json","state":"https://pith.science/pith/QPN4ZJ6SXHH3UDCXWEARHRYK42/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QPN4ZJ6SXHH3UDCXWEARHRYK42/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QPN4ZJ6SXHH3UDCXWEARHRYK42","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":"0100edf94b6f59b44fcda413d3bd4425f91617e845043ede8b43bd25e23a38e3","cross_cats_sorted":["cs.AI","cs.CR","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T16:23:01Z","title_canon_sha256":"c7272c30b4427d40d1e9d5c0b473ac870203536efa3d11cfdf962b184b32cf27"},"schema_version":"1.0","source":{"id":"2404.06430","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.06430","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"arxiv_version","alias_value":"2404.06430v2","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.06430","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"pith_short_12","alias_value":"QPN4ZJ6SXHH3","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"pith_short_16","alias_value":"QPN4ZJ6SXHH3UDCX","created_at":"2026-07-05T09:46:46Z"},{"alias_kind":"pith_short_8","alias_value":"QPN4ZJ6S","created_at":"2026-07-05T09:46:46Z"}],"graph_snapshots":[{"event_id":"sha256:e12a3be73d5adbe84b49f0cd52e8353090a8f735681d626f9e4e28c37e534b71","target":"graph","created_at":"2026-07-05T09:46:46Z","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/2404.06430/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) is an emerging machine learning (ML) training paradigm where clients own their data and collaborate to train a global model, without revealing any data to the server and other participants. Researchers commonly perform experiments in a simulation environment to quickly iterate on ideas. However, existing open-source tools do not offer the efficiency required to simulate FL on larger and more realistic FL datasets. We introduce pfl-research, a fast, modular, and easy-to-use Python framework for simulating FL. It supports TensorFlow, PyTorch, and non-neural network models","authors_text":"\\'Aine Cahill, Congzheng Song, Filip Granqvist, Martin Pelikan, Mona Chitnis, Natarajan Krishnaswami, Rogier Van Dalen, Vojta Jina, Xiaojun Feng, Yi Sheng Chan","cross_cats":["cs.AI","cs.CR","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T16:23:01Z","title":"pfl-research: simulation framework for accelerating research in Private Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.06430","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":"sha256:5e4099429b6341854bd502a6cbb21baad0ef07d0c388ac3a4a3cbcbc611b4191","target":"record","created_at":"2026-07-05T09:46:46Z","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":"0100edf94b6f59b44fcda413d3bd4425f91617e845043ede8b43bd25e23a38e3","cross_cats_sorted":["cs.AI","cs.CR","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T16:23:01Z","title_canon_sha256":"c7272c30b4427d40d1e9d5c0b473ac870203536efa3d11cfdf962b184b32cf27"},"schema_version":"1.0","source":{"id":"2404.06430","kind":"arxiv","version":2}},"canonical_sha256":"83dbcca7d2b9cfba0c57b10113c70ae6876b09513fa95d27fdff825d7765c1ed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"83dbcca7d2b9cfba0c57b10113c70ae6876b09513fa95d27fdff825d7765c1ed","first_computed_at":"2026-07-05T09:46:46.167268Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:46:46.167268Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u3pWpheYUEXpMbxAy/x8Hlfz7RZ7SmmZf4Jyjd9H4cNHBxSFIdvHyRwmK39VGrUsMsO6S7HG+ni970YiB0RfBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:46:46.167801Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.06430","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5e4099429b6341854bd502a6cbb21baad0ef07d0c388ac3a4a3cbcbc611b4191","sha256:e12a3be73d5adbe84b49f0cd52e8353090a8f735681d626f9e4e28c37e534b71"],"state_sha256":"61dc563ecfccf1c1dbdc4c299a9e045485dc940b513ca60fa573791dbf2724dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8mcuOPjJs1oix9Ef6Yt7R8OTlS/tfrMhzWNgpSx+RBvH6pTOssji6v5+nyIz82QhVrdlkvH/AuC+lyVF+JPoAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T04:18:03.019101Z","bundle_sha256":"18ddc9a7bec52c3da55cc3fae10d6d542d4b943c94792e250cd018dee37a2734"}}