{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:P6VDDCZVWG2AMO7QXR2FN4SHW4","short_pith_number":"pith:P6VDDCZV","canonical_record":{"source":{"id":"2505.23849","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-28T21:24:46Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"e9a7c5afe2d4254c458f0c793bf4f02fee14fc2af230c94b728760291d0a918a","abstract_canon_sha256":"8ded574ec0340c922b8f57e8c482c0efc8be524a1f1a8173dc77363216bb85ef"},"schema_version":"1.0"},"canonical_sha256":"7faa318b35b1b4063bf0bc7456f247b731220315b292fbe2d43b00e3e7c9d822","source":{"kind":"arxiv","id":"2505.23849","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.23849","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"arxiv_version","alias_value":"2505.23849v2","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.23849","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_12","alias_value":"P6VDDCZVWG2A","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_16","alias_value":"P6VDDCZVWG2AMO7Q","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_8","alias_value":"P6VDDCZV","created_at":"2026-07-05T11:52:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:P6VDDCZVWG2AMO7QXR2FN4SHW4","target":"record","payload":{"canonical_record":{"source":{"id":"2505.23849","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-28T21:24:46Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"e9a7c5afe2d4254c458f0c793bf4f02fee14fc2af230c94b728760291d0a918a","abstract_canon_sha256":"8ded574ec0340c922b8f57e8c482c0efc8be524a1f1a8173dc77363216bb85ef"},"schema_version":"1.0"},"canonical_sha256":"7faa318b35b1b4063bf0bc7456f247b731220315b292fbe2d43b00e3e7c9d822","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:52:02.450852Z","signature_b64":"Somv3rTkwmIdoU2utA4GzpFEUVEZNASv0yvSF4DtPFSApVVlLHGFt2zUh8VS7GyGelV3a6j4X8B4YGocv6dnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7faa318b35b1b4063bf0bc7456f247b731220315b292fbe2d43b00e3e7c9d822","last_reissued_at":"2026-07-05T11:52:02.450370Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:52:02.450370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.23849","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":"2026-07-05T11:52:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TLexj6sE0UUTJuP+qR7XRxdxDZgHXvDExNaCy2Fkm5WeE479hbIZgOg1F0tmOB0VEs2IGciHWQMLWBJCVv2vBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:00:15.313221Z"},"content_sha256":"1293e7f1e5b399fc04afbf7648bdecfa49afbfe9df35a70b113815c712142836","schema_version":"1.0","event_id":"sha256:1293e7f1e5b399fc04afbf7648bdecfa49afbfe9df35a70b113815c712142836"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:P6VDDCZVWG2AMO7QXR2FN4SHW4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CR","authors_text":"Aditya Sinha, Kaveen Hiniduma, Ravi Madduri, Suren Byna, Zilinghan Li","submitted_at":"2025-05-28T21:24:46Z","abstract_excerpt":"Privacy-Preserving Federated Learning (PPFL) is a decentralized machine learning approach where multiple clients train a model collaboratively. PPFL preserves the privacy and security of a client's data without exchanging it. However, ensuring that data at each client is of high quality and ready for federated learning (FL) is a challenge due to restricted data access. In this paper, we introduce CADRE (Customizable Assurance of Data Readiness) for federated learning (FL), a novel framework that allows users to define custom data readiness (DR) metrics, rules, and remedies tailored to specific"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.23849","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/2505.23849/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":"2026-07-05T11:52:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dt4hy2kaq8xu3EauqtWaBRP/lifcnWFnyN1GvjW6+3h08YWFT9Asa+Ro4YqzaN3sPU/HniAaIbzbl08q5a0RBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:00:15.313746Z"},"content_sha256":"025bda60f4970632d21aa1ef726d80a5beffdf478ef6234d009ff7694d35073d","schema_version":"1.0","event_id":"sha256:025bda60f4970632d21aa1ef726d80a5beffdf478ef6234d009ff7694d35073d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P6VDDCZVWG2AMO7QXR2FN4SHW4/bundle.json","state_url":"https://pith.science/pith/P6VDDCZVWG2AMO7QXR2FN4SHW4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P6VDDCZVWG2AMO7QXR2FN4SHW4/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":"2026-08-07T21:00:15Z","links":{"resolver":"https://pith.science/pith/P6VDDCZVWG2AMO7QXR2FN4SHW4","bundle":"https://pith.science/pith/P6VDDCZVWG2AMO7QXR2FN4SHW4/bundle.json","state":"https://pith.science/pith/P6VDDCZVWG2AMO7QXR2FN4SHW4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P6VDDCZVWG2AMO7QXR2FN4SHW4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:P6VDDCZVWG2AMO7QXR2FN4SHW4","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":"8ded574ec0340c922b8f57e8c482c0efc8be524a1f1a8173dc77363216bb85ef","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-28T21:24:46Z","title_canon_sha256":"e9a7c5afe2d4254c458f0c793bf4f02fee14fc2af230c94b728760291d0a918a"},"schema_version":"1.0","source":{"id":"2505.23849","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.23849","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"arxiv_version","alias_value":"2505.23849v2","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.23849","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_12","alias_value":"P6VDDCZVWG2A","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_16","alias_value":"P6VDDCZVWG2AMO7Q","created_at":"2026-07-05T11:52:02Z"},{"alias_kind":"pith_short_8","alias_value":"P6VDDCZV","created_at":"2026-07-05T11:52:02Z"}],"graph_snapshots":[{"event_id":"sha256:025bda60f4970632d21aa1ef726d80a5beffdf478ef6234d009ff7694d35073d","target":"graph","created_at":"2026-07-05T11:52:02Z","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/2505.23849/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Privacy-Preserving Federated Learning (PPFL) is a decentralized machine learning approach where multiple clients train a model collaboratively. PPFL preserves the privacy and security of a client's data without exchanging it. However, ensuring that data at each client is of high quality and ready for federated learning (FL) is a challenge due to restricted data access. In this paper, we introduce CADRE (Customizable Assurance of Data Readiness) for federated learning (FL), a novel framework that allows users to define custom data readiness (DR) metrics, rules, and remedies tailored to specific","authors_text":"Aditya Sinha, Kaveen Hiniduma, Ravi Madduri, Suren Byna, Zilinghan Li","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-28T21:24:46Z","title":"CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.23849","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":"sha256:1293e7f1e5b399fc04afbf7648bdecfa49afbfe9df35a70b113815c712142836","target":"record","created_at":"2026-07-05T11:52:02Z","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":"8ded574ec0340c922b8f57e8c482c0efc8be524a1f1a8173dc77363216bb85ef","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-28T21:24:46Z","title_canon_sha256":"e9a7c5afe2d4254c458f0c793bf4f02fee14fc2af230c94b728760291d0a918a"},"schema_version":"1.0","source":{"id":"2505.23849","kind":"arxiv","version":2}},"canonical_sha256":"7faa318b35b1b4063bf0bc7456f247b731220315b292fbe2d43b00e3e7c9d822","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7faa318b35b1b4063bf0bc7456f247b731220315b292fbe2d43b00e3e7c9d822","first_computed_at":"2026-07-05T11:52:02.450370Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:52:02.450370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Somv3rTkwmIdoU2utA4GzpFEUVEZNASv0yvSF4DtPFSApVVlLHGFt2zUh8VS7GyGelV3a6j4X8B4YGocv6dnAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:52:02.450852Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.23849","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1293e7f1e5b399fc04afbf7648bdecfa49afbfe9df35a70b113815c712142836","sha256:025bda60f4970632d21aa1ef726d80a5beffdf478ef6234d009ff7694d35073d"],"state_sha256":"c4348d986a274853962f903b3882b54065f58b94ff286843ff91e1f85664ed5a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GiDzMC8i9et0XJoqQQquU0Ck6Utz12LNbAjmcQOoaKmIm2k67GoLYcB+9PFp8SlB8WwM1BXurqzdAKldlpKvAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T21:00:15.319192Z","bundle_sha256":"46165056bfc6b088e7ec15be50189e17478802b974d6700e925d1f5890b5c231"}}