{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:7I7HK4NM5NNG2HIMWRY5AGMSQC","short_pith_number":"pith:7I7HK4NM","canonical_record":{"source":{"id":"2505.06759","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T21:27:40Z","cross_cats_sorted":["cs.CR","cs.DC","cs.IT","math.IT"],"title_canon_sha256":"8543a058b78e4e80846bbde504728c86e4bfbd6e8a03910b17adba2181e9e60c","abstract_canon_sha256":"15c9d9098b98ada5666f40e62fefa5146c194a29e82fdfa497d547e1d5eafb23"},"schema_version":"1.0"},"canonical_sha256":"fa3e7571aceb5a6d1d0cb471d0199280aecb312a084e4117c6bc4cff5e30b2da","source":{"kind":"arxiv","id":"2505.06759","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.06759","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"arxiv_version","alias_value":"2505.06759v1","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.06759","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"pith_short_12","alias_value":"7I7HK4NM5NNG","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"pith_short_16","alias_value":"7I7HK4NM5NNG2HIM","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"pith_short_8","alias_value":"7I7HK4NM","created_at":"2026-07-05T11:01:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:7I7HK4NM5NNG2HIMWRY5AGMSQC","target":"record","payload":{"canonical_record":{"source":{"id":"2505.06759","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T21:27:40Z","cross_cats_sorted":["cs.CR","cs.DC","cs.IT","math.IT"],"title_canon_sha256":"8543a058b78e4e80846bbde504728c86e4bfbd6e8a03910b17adba2181e9e60c","abstract_canon_sha256":"15c9d9098b98ada5666f40e62fefa5146c194a29e82fdfa497d547e1d5eafb23"},"schema_version":"1.0"},"canonical_sha256":"fa3e7571aceb5a6d1d0cb471d0199280aecb312a084e4117c6bc4cff5e30b2da","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:01:15.314015Z","signature_b64":"uqqBtxGITvRir4QviE5TPlGnsHfRaOUg7KU/9RHqEFG734GAo2lMl6rFhpFSayaMD9TbJiV+sAXJ1j+fjLb5Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa3e7571aceb5a6d1d0cb471d0199280aecb312a084e4117c6bc4cff5e30b2da","last_reissued_at":"2026-07-05T11:01:15.313494Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:01:15.313494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.06759","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":"2026-07-05T11:01:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kddTxz27A5vfkhjP1smyrFvqYODbwbGwBaHMcDRy4ZRi2qs8q39sK61dGjUAjdRzbzV3DXThq5BJ9GdQdAstAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T19:02:42.551466Z"},"content_sha256":"128f4be64d05c2232e4c8d45a866612bd0de59d578d3c9e6d5b6769a93aa154d","schema_version":"1.0","event_id":"sha256:128f4be64d05c2232e4c8d45a866612bd0de59d578d3c9e6d5b6769a93aa154d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:7I7HK4NM5NNG2HIMWRY5AGMSQC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Privacy-aware Berrut Approximated Coded Computing applied to general distributed learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CR","cs.DC","cs.IT","math.IT"],"primary_cat":"cs.LG","authors_text":"Ana Fern\\'andez-Vilas, Manuel Fern\\'andez-Veiga, Rebeca P. D\\'iaz-Redondo, Xavier Mart\\'inez-Lua\\~na","submitted_at":"2025-05-10T21:27:40Z","abstract_excerpt":"Coded computing is one of the techniques that can be used for privacy protection in Federated Learning. However, most of the constructions used for coded computing work only under the assumption that the computations involved are exact, generally restricted to special classes of functions, and require quantized inputs. This paper considers the use of Private Berrut Approximate Coded Computing (PBACC) as a general solution to add strong but non-perfect privacy to federated learning. We derive new adapted PBACC algorithms for centralized aggregation, secure distributed training with centralized "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.06759","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/2505.06759/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":"2026-07-05T11:01:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oQFma+mqe3SXQNtAqraXqhxbtwgxh+47cNMQsFx99gbxgtSxna9LadoRkhEmlzuDGGlXr2spQS0gi8iFsgz2Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T19:02:42.551997Z"},"content_sha256":"bf6b6946511416eda7b9a73d8f98a5eb86a89400def1266d4915593088930183","schema_version":"1.0","event_id":"sha256:bf6b6946511416eda7b9a73d8f98a5eb86a89400def1266d4915593088930183"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7I7HK4NM5NNG2HIMWRY5AGMSQC/bundle.json","state_url":"https://pith.science/pith/7I7HK4NM5NNG2HIMWRY5AGMSQC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7I7HK4NM5NNG2HIMWRY5AGMSQC/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":"2026-08-03T19:02:42Z","links":{"resolver":"https://pith.science/pith/7I7HK4NM5NNG2HIMWRY5AGMSQC","bundle":"https://pith.science/pith/7I7HK4NM5NNG2HIMWRY5AGMSQC/bundle.json","state":"https://pith.science/pith/7I7HK4NM5NNG2HIMWRY5AGMSQC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7I7HK4NM5NNG2HIMWRY5AGMSQC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:7I7HK4NM5NNG2HIMWRY5AGMSQC","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":"15c9d9098b98ada5666f40e62fefa5146c194a29e82fdfa497d547e1d5eafb23","cross_cats_sorted":["cs.CR","cs.DC","cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T21:27:40Z","title_canon_sha256":"8543a058b78e4e80846bbde504728c86e4bfbd6e8a03910b17adba2181e9e60c"},"schema_version":"1.0","source":{"id":"2505.06759","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.06759","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"arxiv_version","alias_value":"2505.06759v1","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.06759","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"pith_short_12","alias_value":"7I7HK4NM5NNG","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"pith_short_16","alias_value":"7I7HK4NM5NNG2HIM","created_at":"2026-07-05T11:01:15Z"},{"alias_kind":"pith_short_8","alias_value":"7I7HK4NM","created_at":"2026-07-05T11:01:15Z"}],"graph_snapshots":[{"event_id":"sha256:bf6b6946511416eda7b9a73d8f98a5eb86a89400def1266d4915593088930183","target":"graph","created_at":"2026-07-05T11:01:15Z","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/2505.06759/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Coded computing is one of the techniques that can be used for privacy protection in Federated Learning. However, most of the constructions used for coded computing work only under the assumption that the computations involved are exact, generally restricted to special classes of functions, and require quantized inputs. This paper considers the use of Private Berrut Approximate Coded Computing (PBACC) as a general solution to add strong but non-perfect privacy to federated learning. We derive new adapted PBACC algorithms for centralized aggregation, secure distributed training with centralized ","authors_text":"Ana Fern\\'andez-Vilas, Manuel Fern\\'andez-Veiga, Rebeca P. D\\'iaz-Redondo, Xavier Mart\\'inez-Lua\\~na","cross_cats":["cs.CR","cs.DC","cs.IT","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T21:27:40Z","title":"Privacy-aware Berrut Approximated Coded Computing applied to general distributed learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.06759","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":"sha256:128f4be64d05c2232e4c8d45a866612bd0de59d578d3c9e6d5b6769a93aa154d","target":"record","created_at":"2026-07-05T11:01:15Z","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":"15c9d9098b98ada5666f40e62fefa5146c194a29e82fdfa497d547e1d5eafb23","cross_cats_sorted":["cs.CR","cs.DC","cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-10T21:27:40Z","title_canon_sha256":"8543a058b78e4e80846bbde504728c86e4bfbd6e8a03910b17adba2181e9e60c"},"schema_version":"1.0","source":{"id":"2505.06759","kind":"arxiv","version":1}},"canonical_sha256":"fa3e7571aceb5a6d1d0cb471d0199280aecb312a084e4117c6bc4cff5e30b2da","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa3e7571aceb5a6d1d0cb471d0199280aecb312a084e4117c6bc4cff5e30b2da","first_computed_at":"2026-07-05T11:01:15.313494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:01:15.313494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uqqBtxGITvRir4QviE5TPlGnsHfRaOUg7KU/9RHqEFG734GAo2lMl6rFhpFSayaMD9TbJiV+sAXJ1j+fjLb5Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:01:15.314015Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.06759","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:128f4be64d05c2232e4c8d45a866612bd0de59d578d3c9e6d5b6769a93aa154d","sha256:bf6b6946511416eda7b9a73d8f98a5eb86a89400def1266d4915593088930183"],"state_sha256":"f9dd8fbd34a1c0e573d282e19b23efac706db3e7fe8d8589aa6061c9d3bda012"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iYIo92J9uMpgRQJkBYi4q6OAkeFahGzGbZnxeCjxuWbHfsW4cJ5MgpSVi8juJcRlw50Q+epR2teVQYnoe9t9BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T19:02:42.557157Z","bundle_sha256":"ba6fae0737d8b652600a5b55bce40b628e6518f55c0e4ba23f68d8b95d01dcb0"}}