{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:BZWLOZKAJKKDJTUWGLPDDDIVFD","short_pith_number":"pith:BZWLOZKA","canonical_record":{"source":{"id":"2205.13722","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-27T02:32:26Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"aa3d6c391960547a18d07c4db9e6b4aabe0d7eceddabf998b17ec8141cfe09e8","abstract_canon_sha256":"4904ef67ffc6bcfd9cfd0b220ec24928d0a51b008116d141a0517562a9f1ea3c"},"schema_version":"1.0"},"canonical_sha256":"0e6cb765404a9434ce9632de318d1528ce83cb0616fbaf7b330b9ad5f283cf74","source":{"kind":"arxiv","id":"2205.13722","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.13722","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"arxiv_version","alias_value":"2205.13722v2","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.13722","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"pith_short_12","alias_value":"BZWLOZKAJKKD","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"pith_short_16","alias_value":"BZWLOZKAJKKDJTUW","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"pith_short_8","alias_value":"BZWLOZKA","created_at":"2026-07-05T05:38:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:BZWLOZKAJKKDJTUWGLPDDDIVFD","target":"record","payload":{"canonical_record":{"source":{"id":"2205.13722","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-27T02:32:26Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"aa3d6c391960547a18d07c4db9e6b4aabe0d7eceddabf998b17ec8141cfe09e8","abstract_canon_sha256":"4904ef67ffc6bcfd9cfd0b220ec24928d0a51b008116d141a0517562a9f1ea3c"},"schema_version":"1.0"},"canonical_sha256":"0e6cb765404a9434ce9632de318d1528ce83cb0616fbaf7b330b9ad5f283cf74","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:38:08.570641Z","signature_b64":"OF9thMoyNl0tZLZA2moU15yRYmePD6co53eRNfn4ZpsMOGtuzyWhxszLnuYwQj+3VFLoegn22RTMzE84yY5lDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e6cb765404a9434ce9632de318d1528ce83cb0616fbaf7b330b9ad5f283cf74","last_reissued_at":"2026-07-05T05:38:08.570156Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:38:08.570156Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.13722","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":"2026-07-05T05:38:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cBMMxB0GB8lvwbRkzh11/IbE224ukz6x0YTQM/DaJ/pLB8Yu9zLHvQEHLC4T+4Mkgk8G45qsrnMZ+5yIbD2ACQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T07:43:52.580481Z"},"content_sha256":"e6e6f7e802d5d180a0b40a16034ddd4fec64681d1a9402cbd64eae3cfece8ce7","schema_version":"1.0","event_id":"sha256:e6e6f7e802d5d180a0b40a16034ddd4fec64681d1a9402cbd64eae3cfece8ce7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:BZWLOZKAJKKDJTUWGLPDDDIVFD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can Foundation Models Help Us Achieve Perfect Secrecy?","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Christopher R\\'e, Simran Arora","submitted_at":"2022-05-27T02:32:26Z","abstract_excerpt":"A key promise of machine learning is the ability to assist users with personal tasks. Because the personal context required to make accurate predictions is often sensitive, we require systems that protect privacy. A gold standard privacy-preserving system will satisfy perfect secrecy, meaning that interactions with the system provably reveal no private information. However, privacy and quality appear to be in tension in existing systems for personal tasks. Neural models typically require copious amounts of training to perform well, while individual users typically hold a limited scale of data,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.13722","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/2205.13722/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":"2026-07-05T05:38:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jANhktpY6S3ztyPOV4yxCNvzkADzdyMGkAuz+bAC1gQEOMGbeEnZtY9SGa6Za9Gyez4uYQRKBlVszbecWLBUBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T07:43:52.580863Z"},"content_sha256":"a575ff0e7a9cfb517d42a502ef22a8ead17dfd6323f17f6f59f1f8916946ab37","schema_version":"1.0","event_id":"sha256:a575ff0e7a9cfb517d42a502ef22a8ead17dfd6323f17f6f59f1f8916946ab37"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BZWLOZKAJKKDJTUWGLPDDDIVFD/bundle.json","state_url":"https://pith.science/pith/BZWLOZKAJKKDJTUWGLPDDDIVFD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BZWLOZKAJKKDJTUWGLPDDDIVFD/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":"2026-07-28T07:43:52Z","links":{"resolver":"https://pith.science/pith/BZWLOZKAJKKDJTUWGLPDDDIVFD","bundle":"https://pith.science/pith/BZWLOZKAJKKDJTUWGLPDDDIVFD/bundle.json","state":"https://pith.science/pith/BZWLOZKAJKKDJTUWGLPDDDIVFD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BZWLOZKAJKKDJTUWGLPDDDIVFD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:BZWLOZKAJKKDJTUWGLPDDDIVFD","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":"4904ef67ffc6bcfd9cfd0b220ec24928d0a51b008116d141a0517562a9f1ea3c","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-27T02:32:26Z","title_canon_sha256":"aa3d6c391960547a18d07c4db9e6b4aabe0d7eceddabf998b17ec8141cfe09e8"},"schema_version":"1.0","source":{"id":"2205.13722","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.13722","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"arxiv_version","alias_value":"2205.13722v2","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.13722","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"pith_short_12","alias_value":"BZWLOZKAJKKD","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"pith_short_16","alias_value":"BZWLOZKAJKKDJTUW","created_at":"2026-07-05T05:38:08Z"},{"alias_kind":"pith_short_8","alias_value":"BZWLOZKA","created_at":"2026-07-05T05:38:08Z"}],"graph_snapshots":[{"event_id":"sha256:a575ff0e7a9cfb517d42a502ef22a8ead17dfd6323f17f6f59f1f8916946ab37","target":"graph","created_at":"2026-07-05T05:38:08Z","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/2205.13722/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A key promise of machine learning is the ability to assist users with personal tasks. Because the personal context required to make accurate predictions is often sensitive, we require systems that protect privacy. A gold standard privacy-preserving system will satisfy perfect secrecy, meaning that interactions with the system provably reveal no private information. However, privacy and quality appear to be in tension in existing systems for personal tasks. Neural models typically require copious amounts of training to perform well, while individual users typically hold a limited scale of data,","authors_text":"Christopher R\\'e, Simran Arora","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-27T02:32:26Z","title":"Can Foundation Models Help Us Achieve Perfect Secrecy?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.13722","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:e6e6f7e802d5d180a0b40a16034ddd4fec64681d1a9402cbd64eae3cfece8ce7","target":"record","created_at":"2026-07-05T05:38:08Z","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":"4904ef67ffc6bcfd9cfd0b220ec24928d0a51b008116d141a0517562a9f1ea3c","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-27T02:32:26Z","title_canon_sha256":"aa3d6c391960547a18d07c4db9e6b4aabe0d7eceddabf998b17ec8141cfe09e8"},"schema_version":"1.0","source":{"id":"2205.13722","kind":"arxiv","version":2}},"canonical_sha256":"0e6cb765404a9434ce9632de318d1528ce83cb0616fbaf7b330b9ad5f283cf74","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e6cb765404a9434ce9632de318d1528ce83cb0616fbaf7b330b9ad5f283cf74","first_computed_at":"2026-07-05T05:38:08.570156Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:38:08.570156Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OF9thMoyNl0tZLZA2moU15yRYmePD6co53eRNfn4ZpsMOGtuzyWhxszLnuYwQj+3VFLoegn22RTMzE84yY5lDA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:38:08.570641Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.13722","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e6e6f7e802d5d180a0b40a16034ddd4fec64681d1a9402cbd64eae3cfece8ce7","sha256:a575ff0e7a9cfb517d42a502ef22a8ead17dfd6323f17f6f59f1f8916946ab37"],"state_sha256":"fdfefd5c80b93e66a30ab2887ca97d0afef52f30434d79d3a81a579c26dc95a0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AlxLlxdYvploUZDL887h6MbQEnl4S7Zy6yeVZq+mlbmaT+NDXqgQjJZZisZesrl/hpe/CtWDpHpNqmF0D+LECQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-28T07:43:52.583695Z","bundle_sha256":"c671859721dc9f7efc1ecabaa0b2f4196370a65ec5f6afc7485955461769cb89"}}