{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:DDG67ZDCJDZC4A2DMDUWZGXYMH","short_pith_number":"pith:DDG67ZDC","canonical_record":{"source":{"id":"2210.15034","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2022-10-26T21:06:38Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"53a146c55beba932c3aef5fcc005b7887a800166d8256962ddea4d3d898bab7a","abstract_canon_sha256":"2f34262f2f7d1e3211a464ad5b5770fcc0608acd052a27648b421dc7953db1e5"},"schema_version":"1.0"},"canonical_sha256":"18cdefe46248f22e034360e96c9af861e4a345e55a1c95a8946e1c945d3237a2","source":{"kind":"arxiv","id":"2210.15034","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.15034","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"arxiv_version","alias_value":"2210.15034v3","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.15034","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"pith_short_12","alias_value":"DDG67ZDCJDZC","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"pith_short_16","alias_value":"DDG67ZDCJDZC4A2D","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"pith_short_8","alias_value":"DDG67ZDC","created_at":"2026-07-05T06:17:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:DDG67ZDCJDZC4A2DMDUWZGXYMH","target":"record","payload":{"canonical_record":{"source":{"id":"2210.15034","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2022-10-26T21:06:38Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"53a146c55beba932c3aef5fcc005b7887a800166d8256962ddea4d3d898bab7a","abstract_canon_sha256":"2f34262f2f7d1e3211a464ad5b5770fcc0608acd052a27648b421dc7953db1e5"},"schema_version":"1.0"},"canonical_sha256":"18cdefe46248f22e034360e96c9af861e4a345e55a1c95a8946e1c945d3237a2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:17:02.446395Z","signature_b64":"eiI0+0YKkcjd29ZMD+TUot+2coHsdpdRctGLZ31Lbed1MzGpnyF2edDT1fmzatDGZdtGzpkAIhRF9ffLgPdEDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"18cdefe46248f22e034360e96c9af861e4a345e55a1c95a8946e1c945d3237a2","last_reissued_at":"2026-07-05T06:17:02.445982Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:17:02.445982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.15034","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:17:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s4a2eshynBXxk1evkzcWMIdsJCuFvtMlXwp1aAlaCNGchJssPZwithlAZtVEseVj65J0u7ceQCqwPBT4VDHNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:30:46.094581Z"},"content_sha256":"bcad349bdd169290fceed51ec0cbfa541e47c64c2469dffd1f2b349a7ec872d4","schema_version":"1.0","event_id":"sha256:bcad349bdd169290fceed51ec0cbfa541e47c64c2469dffd1f2b349a7ec872d4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:DDG67ZDCJDZC4A2DMDUWZGXYMH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"InfoShape: Task-Based Neural Data Shaping via Mutual Information","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Homa Esfahanizadeh, Manya Ghobadi, Muriel Medard, Regina Barzilay, William Wu","submitted_at":"2022-10-26T21:06:38Z","abstract_excerpt":"The use of mutual information as a tool in private data sharing has remained an open challenge due to the difficulty of its estimation in practice. In this paper, we propose InfoShape, a task-based encoder that aims to remove unnecessary sensitive information from training data while maintaining enough relevant information for a particular ML training task. We achieve this goal by utilizing mutual information estimators that are based on neural networks, in order to measure two performance metrics, privacy and utility. Using these together in a Lagrangian optimization, we train a separate neur"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.15034","kind":"arxiv","version":3},"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/2210.15034/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":"2026-07-05T06:17:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HwxHHIV6V4dGKXf41EF9RlDRc4oA0eeaWINBcKGVMFm/Jxyrg5drCOP2Qrh5ORckhoZR3z/958rInQ3B8/AeAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:30:46.095171Z"},"content_sha256":"46a436f5df3ccad25efae79d5c92148616f2c355803a2277e4011d93a4fa304f","schema_version":"1.0","event_id":"sha256:46a436f5df3ccad25efae79d5c92148616f2c355803a2277e4011d93a4fa304f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DDG67ZDCJDZC4A2DMDUWZGXYMH/bundle.json","state_url":"https://pith.science/pith/DDG67ZDCJDZC4A2DMDUWZGXYMH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DDG67ZDCJDZC4A2DMDUWZGXYMH/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":"2026-08-05T18:30:46Z","links":{"resolver":"https://pith.science/pith/DDG67ZDCJDZC4A2DMDUWZGXYMH","bundle":"https://pith.science/pith/DDG67ZDCJDZC4A2DMDUWZGXYMH/bundle.json","state":"https://pith.science/pith/DDG67ZDCJDZC4A2DMDUWZGXYMH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DDG67ZDCJDZC4A2DMDUWZGXYMH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:DDG67ZDCJDZC4A2DMDUWZGXYMH","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":"2f34262f2f7d1e3211a464ad5b5770fcc0608acd052a27648b421dc7953db1e5","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2022-10-26T21:06:38Z","title_canon_sha256":"53a146c55beba932c3aef5fcc005b7887a800166d8256962ddea4d3d898bab7a"},"schema_version":"1.0","source":{"id":"2210.15034","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.15034","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"arxiv_version","alias_value":"2210.15034v3","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.15034","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"pith_short_12","alias_value":"DDG67ZDCJDZC","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"pith_short_16","alias_value":"DDG67ZDCJDZC4A2D","created_at":"2026-07-05T06:17:02Z"},{"alias_kind":"pith_short_8","alias_value":"DDG67ZDC","created_at":"2026-07-05T06:17:02Z"}],"graph_snapshots":[{"event_id":"sha256:46a436f5df3ccad25efae79d5c92148616f2c355803a2277e4011d93a4fa304f","target":"graph","created_at":"2026-07-05T06:17:02Z","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/2210.15034/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The use of mutual information as a tool in private data sharing has remained an open challenge due to the difficulty of its estimation in practice. In this paper, we propose InfoShape, a task-based encoder that aims to remove unnecessary sensitive information from training data while maintaining enough relevant information for a particular ML training task. We achieve this goal by utilizing mutual information estimators that are based on neural networks, in order to measure two performance metrics, privacy and utility. Using these together in a Lagrangian optimization, we train a separate neur","authors_text":"Homa Esfahanizadeh, Manya Ghobadi, Muriel Medard, Regina Barzilay, William Wu","cross_cats":["math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2022-10-26T21:06:38Z","title":"InfoShape: Task-Based Neural Data Shaping via Mutual Information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.15034","kind":"arxiv","version":3},"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:bcad349bdd169290fceed51ec0cbfa541e47c64c2469dffd1f2b349a7ec872d4","target":"record","created_at":"2026-07-05T06:17:02Z","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":"2f34262f2f7d1e3211a464ad5b5770fcc0608acd052a27648b421dc7953db1e5","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2022-10-26T21:06:38Z","title_canon_sha256":"53a146c55beba932c3aef5fcc005b7887a800166d8256962ddea4d3d898bab7a"},"schema_version":"1.0","source":{"id":"2210.15034","kind":"arxiv","version":3}},"canonical_sha256":"18cdefe46248f22e034360e96c9af861e4a345e55a1c95a8946e1c945d3237a2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"18cdefe46248f22e034360e96c9af861e4a345e55a1c95a8946e1c945d3237a2","first_computed_at":"2026-07-05T06:17:02.445982Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:17:02.445982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eiI0+0YKkcjd29ZMD+TUot+2coHsdpdRctGLZ31Lbed1MzGpnyF2edDT1fmzatDGZdtGzpkAIhRF9ffLgPdEDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:17:02.446395Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.15034","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bcad349bdd169290fceed51ec0cbfa541e47c64c2469dffd1f2b349a7ec872d4","sha256:46a436f5df3ccad25efae79d5c92148616f2c355803a2277e4011d93a4fa304f"],"state_sha256":"26c744b41006381d36e0bd80490fa003e2d5bab1abb2d717967d144e8935bbf6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oeVVOMa5qdUyXDHPpMhTot7T88oFvqiLghxRonNKOtIoMWlV26DNqCcP5bqM7stNMOHRF7gUezabA1tXtSZZDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T18:30:46.101882Z","bundle_sha256":"4b73c388eef8dab98546fd64d3769ba2fd2b238984c87ecca49a4ca75214c6f7"}}