{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:W63OAPRXLM4MTCTQI2NIHRWOTD","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":"76ca9b61a0187ad205e4c6ce09da261c8e9f79d6a7fea6a2eba9a15bd51e5004","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-15T14:56:44Z","title_canon_sha256":"d7eb4362db44a2361716c9d8a9733980439b8d8e383c3235240efcf3173ccc39"},"schema_version":"1.0","source":{"id":"1911.06679","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.06679","created_at":"2026-07-05T00:38:34Z"},{"alias_kind":"arxiv_version","alias_value":"1911.06679v2","created_at":"2026-07-05T00:38:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.06679","created_at":"2026-07-05T00:38:34Z"},{"alias_kind":"pith_short_12","alias_value":"W63OAPRXLM4M","created_at":"2026-07-05T00:38:34Z"},{"alias_kind":"pith_short_16","alias_value":"W63OAPRXLM4MTCTQ","created_at":"2026-07-05T00:38:34Z"},{"alias_kind":"pith_short_8","alias_value":"W63OAPRX","created_at":"2026-07-05T00:38:34Z"}],"graph_snapshots":[{"event_id":"sha256:22c81eaf005a7eb3889ba73531e6a8a227ceb243ae59f5efe12c2a2c5822cd83","target":"graph","created_at":"2026-07-05T00:38:34Z","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/1911.06679/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To improve real-world applications of machine learning, experienced modelers develop intuition about their datasets, their models, and how the two interact. Manual inspection of raw data - of representative samples, of outliers, of misclassifications - is an essential tool in a) identifying and fixing problems in the data, b) generating new modeling hypotheses, and c) assigning or refining human-provided labels. However, manual data inspection is problematic for privacy sensitive datasets, such as those representing the behavior of real-world individuals. Furthermore, manual data inspection is","authors_text":"Blaise Aguera y Arcas, Daniel Ramage, H. Brendan McMahan, Mingqing Chen, Peter Kairouz, Rajiv Mathews, Sean Augenstein, Swaroop Ramaswamy","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-15T14:56:44Z","title":"Generative Models for Effective ML on Private, Decentralized Datasets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.06679","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":"sha256:329c84533e14a39c22298c1d922243049a7aa4ee6750a4c6410193fb30ae9110","target":"record","created_at":"2026-07-05T00:38:34Z","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":"76ca9b61a0187ad205e4c6ce09da261c8e9f79d6a7fea6a2eba9a15bd51e5004","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-15T14:56:44Z","title_canon_sha256":"d7eb4362db44a2361716c9d8a9733980439b8d8e383c3235240efcf3173ccc39"},"schema_version":"1.0","source":{"id":"1911.06679","kind":"arxiv","version":2}},"canonical_sha256":"b7b6e03e375b38c98a70469a83c6ce98fd0e1406f4bce94a3774a4f992183117","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7b6e03e375b38c98a70469a83c6ce98fd0e1406f4bce94a3774a4f992183117","first_computed_at":"2026-07-05T00:38:34.822987Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:38:34.822987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iUSQAPlAyhhRjpSivqanbRzKbAWas1Zyf3Rphay7ZawmW/SzsOFJ10Ykm+6OgUmb4b4/2MuCyuT3SNnEqY2xCA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:38:34.823525Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.06679","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:329c84533e14a39c22298c1d922243049a7aa4ee6750a4c6410193fb30ae9110","sha256:22c81eaf005a7eb3889ba73531e6a8a227ceb243ae59f5efe12c2a2c5822cd83"],"state_sha256":"c13eb65a843f91e0e6b4b68f820266ade4ff1a325edde6370cdce031d7435e68"}