{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:VK2IX65TWQCC4U7SKOZFVRVG3Z","short_pith_number":"pith:VK2IX65T","canonical_record":{"source":{"id":"2205.11518","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-05-23T13:52:46Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"c60c79df3e8a28cb7db7c42cd8a9f96b9c26250c51d4e8bff14ea917e19d8d5b","abstract_canon_sha256":"5cdaed1b6dc039adffcbfa3a158e27cb3140bf6171a8f8d095e87dac88edb60c"},"schema_version":"1.0"},"canonical_sha256":"aab48bfbb3b4042e53f253b25ac6a6de74a6c7c784eb34aacca68e0ad7fd4080","source":{"kind":"arxiv","id":"2205.11518","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11518","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11518v4","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11518","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"pith_short_12","alias_value":"VK2IX65TWQCC","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"pith_short_16","alias_value":"VK2IX65TWQCC4U7S","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"pith_short_8","alias_value":"VK2IX65T","created_at":"2026-06-05T01:15:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:VK2IX65TWQCC4U7SKOZFVRVG3Z","target":"record","payload":{"canonical_record":{"source":{"id":"2205.11518","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-05-23T13:52:46Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"c60c79df3e8a28cb7db7c42cd8a9f96b9c26250c51d4e8bff14ea917e19d8d5b","abstract_canon_sha256":"5cdaed1b6dc039adffcbfa3a158e27cb3140bf6171a8f8d095e87dac88edb60c"},"schema_version":"1.0"},"canonical_sha256":"aab48bfbb3b4042e53f253b25ac6a6de74a6c7c784eb34aacca68e0ad7fd4080","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:15:10.842972Z","signature_b64":"yMwAvGCRDsGRTODyEno5qB0sGRRZQ187EnRBb9PciEO9MLPx9OdPa2OT2C6Tb3VEeCx3S7uCCgl5u4RUyayPDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aab48bfbb3b4042e53f253b25ac6a6de74a6c7c784eb34aacca68e0ad7fd4080","last_reissued_at":"2026-06-05T01:15:10.842512Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:15:10.842512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.11518","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-05T01:15:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m/EnOeZgWLSb1EqZ0wtuQvR9rnRNPnj5K8g0h3Mt1cjCdUxzFIVrPVk6cjnaxlbyLHGmopK+d0euFXxvfDX0BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T21:28:28.533214Z"},"content_sha256":"61a03cbef9fa81171f7461c1cb44cb182b8ffec1000c702f84b5ccd368e5ba6a","schema_version":"1.0","event_id":"sha256:61a03cbef9fa81171f7461c1cb44cb182b8ffec1000c702f84b5ccd368e5ba6a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:VK2IX65TWQCC4U7SKOZFVRVG3Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CR","authors_text":"Boi Faltings, Ljubomir Rokvic, Panayiotis Danassis, Sai Praneeth Karimireddy","submitted_at":"2022-05-23T13:52:46Z","abstract_excerpt":"In Federated Learning, it is crucial to handle low-quality, corrupted, or malicious data. However, traditional data valuation methods are not suitable due to privacy concerns. To address this, we propose a simple yet effective approach that utilizes a new influence approximation called \"lazy influence\" to filter and score data while preserving privacy. To do this, each participant uses their own data to estimate the influence of another participant's batch and sends a differentially private obfuscated score to the central coordinator. Our method has been shown to successfully filter out biased"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11518","kind":"arxiv","version":4},"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/2205.11518/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":"2026-06-05T01:15:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yjSPfTTzuiJpVZxAE2HlzHPY+inB+bJrnp15MgR+0VZPRtLX5YE4mtwDTBdWhkQXsTjsG3U4g3zablWYEQiMAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T21:28:28.534513Z"},"content_sha256":"8589357136552253882433b1757f8cf7d791195b157427fd492bc67ba6cd8202","schema_version":"1.0","event_id":"sha256:8589357136552253882433b1757f8cf7d791195b157427fd492bc67ba6cd8202"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VK2IX65TWQCC4U7SKOZFVRVG3Z/bundle.json","state_url":"https://pith.science/pith/VK2IX65TWQCC4U7SKOZFVRVG3Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VK2IX65TWQCC4U7SKOZFVRVG3Z/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":"2026-06-05T21:28:28Z","links":{"resolver":"https://pith.science/pith/VK2IX65TWQCC4U7SKOZFVRVG3Z","bundle":"https://pith.science/pith/VK2IX65TWQCC4U7SKOZFVRVG3Z/bundle.json","state":"https://pith.science/pith/VK2IX65TWQCC4U7SKOZFVRVG3Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VK2IX65TWQCC4U7SKOZFVRVG3Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:VK2IX65TWQCC4U7SKOZFVRVG3Z","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":"5cdaed1b6dc039adffcbfa3a158e27cb3140bf6171a8f8d095e87dac88edb60c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-05-23T13:52:46Z","title_canon_sha256":"c60c79df3e8a28cb7db7c42cd8a9f96b9c26250c51d4e8bff14ea917e19d8d5b"},"schema_version":"1.0","source":{"id":"2205.11518","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11518","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11518v4","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11518","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"pith_short_12","alias_value":"VK2IX65TWQCC","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"pith_short_16","alias_value":"VK2IX65TWQCC4U7S","created_at":"2026-06-05T01:15:10Z"},{"alias_kind":"pith_short_8","alias_value":"VK2IX65T","created_at":"2026-06-05T01:15:10Z"}],"graph_snapshots":[{"event_id":"sha256:8589357136552253882433b1757f8cf7d791195b157427fd492bc67ba6cd8202","target":"graph","created_at":"2026-06-05T01:15:10Z","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/2205.11518/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In Federated Learning, it is crucial to handle low-quality, corrupted, or malicious data. However, traditional data valuation methods are not suitable due to privacy concerns. To address this, we propose a simple yet effective approach that utilizes a new influence approximation called \"lazy influence\" to filter and score data while preserving privacy. To do this, each participant uses their own data to estimate the influence of another participant's batch and sends a differentially private obfuscated score to the central coordinator. Our method has been shown to successfully filter out biased","authors_text":"Boi Faltings, Ljubomir Rokvic, Panayiotis Danassis, Sai Praneeth Karimireddy","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-05-23T13:52:46Z","title":"LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11518","kind":"arxiv","version":4},"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":"sha256:61a03cbef9fa81171f7461c1cb44cb182b8ffec1000c702f84b5ccd368e5ba6a","target":"record","created_at":"2026-06-05T01:15:10Z","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":"5cdaed1b6dc039adffcbfa3a158e27cb3140bf6171a8f8d095e87dac88edb60c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-05-23T13:52:46Z","title_canon_sha256":"c60c79df3e8a28cb7db7c42cd8a9f96b9c26250c51d4e8bff14ea917e19d8d5b"},"schema_version":"1.0","source":{"id":"2205.11518","kind":"arxiv","version":4}},"canonical_sha256":"aab48bfbb3b4042e53f253b25ac6a6de74a6c7c784eb34aacca68e0ad7fd4080","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aab48bfbb3b4042e53f253b25ac6a6de74a6c7c784eb34aacca68e0ad7fd4080","first_computed_at":"2026-06-05T01:15:10.842512Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:15:10.842512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yMwAvGCRDsGRTODyEno5qB0sGRRZQ187EnRBb9PciEO9MLPx9OdPa2OT2C6Tb3VEeCx3S7uCCgl5u4RUyayPDA==","signature_status":"signed_v1","signed_at":"2026-06-05T01:15:10.842972Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.11518","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:61a03cbef9fa81171f7461c1cb44cb182b8ffec1000c702f84b5ccd368e5ba6a","sha256:8589357136552253882433b1757f8cf7d791195b157427fd492bc67ba6cd8202"],"state_sha256":"1bcc6e9955d13dd7eed2a7ff3b91944d2e6efad58b5734a6e0715feffacd9524"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y3ixwph40LNXn1/SkAL3zaxxTCtYs95zYAkxtTK/VQFk5eEQ4kur0LR9+H7F73ZweYkQ2E8asxd/p5nsmQqLCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T21:28:28.538565Z","bundle_sha256":"a4a1c5204b5186c42c9973460c2bfbe20f9d178155ae8acf292412b8fa59d727"}}