{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:CSBNAV3TAZHBE5MWX3VJCEM6IO","short_pith_number":"pith:CSBNAV3T","canonical_record":{"source":{"id":"2104.00489","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-04-01T14:21:33Z","cross_cats_sorted":["cs.CR","cs.DC"],"title_canon_sha256":"385bff89fe34006cdbe681cbe147af1d04e71293f82f8cb60f89d7eb0d19d29b","abstract_canon_sha256":"4783e487867cdc41188a21a3f624fc43e18095e3a9347c33b94fc84e844e6f43"},"schema_version":"1.0"},"canonical_sha256":"1482d05773064e127596beea91119e43a9f5b9bc8233257fc4ed621ac200c460","source":{"kind":"arxiv","id":"2104.00489","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.00489","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"arxiv_version","alias_value":"2104.00489v3","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.00489","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"pith_short_12","alias_value":"CSBNAV3TAZHB","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"pith_short_16","alias_value":"CSBNAV3TAZHBE5MW","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"pith_short_8","alias_value":"CSBNAV3T","created_at":"2026-07-05T02:32:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:CSBNAV3TAZHBE5MWX3VJCEM6IO","target":"record","payload":{"canonical_record":{"source":{"id":"2104.00489","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-04-01T14:21:33Z","cross_cats_sorted":["cs.CR","cs.DC"],"title_canon_sha256":"385bff89fe34006cdbe681cbe147af1d04e71293f82f8cb60f89d7eb0d19d29b","abstract_canon_sha256":"4783e487867cdc41188a21a3f624fc43e18095e3a9347c33b94fc84e844e6f43"},"schema_version":"1.0"},"canonical_sha256":"1482d05773064e127596beea91119e43a9f5b9bc8233257fc4ed621ac200c460","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:32:04.866061Z","signature_b64":"8Ts1A+JttabX56Vc2NnsVlcbvWdNYDq5Ez5AWqQ2lNnFaZ98pWj8zkxkt6OSyLAfHrg0YpBiOPbMDTEBPROPCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1482d05773064e127596beea91119e43a9f5b9bc8233257fc4ed621ac200c460","last_reissued_at":"2026-07-05T02:32:04.865665Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:32:04.865665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.00489","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":"2026-07-05T02:32:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DSbnkipiVr+MheIDHUTfz8XVAbxakNQOakq64sPsiu0NhV4PbYf7aa2ALkxsbdGhlsXssExlAqcPc6DSvCirAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:12:24.508237Z"},"content_sha256":"92f8eaa622ecaa76d8a7ad418ec46f477a34cb69ecd8d074b530a8ae457bb63a","schema_version":"1.0","event_id":"sha256:92f8eaa622ecaa76d8a7ad418ec46f477a34cb69ecd8d074b530a8ae457bb63a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:CSBNAV3TAZHBE5MWX3VJCEM6IO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CR","cs.DC"],"primary_cat":"cs.LG","authors_text":"Abbas Ismail, Adam James Hall, Daniele Romanini, Michael A. Hoeh, Pavlos Papadopoulos, Robert Sandmann, Robin Roehm, Tom Titcombe, Tudor Cebere","submitted_at":"2021-04-01T14:21:33Z","abstract_excerpt":"We introduce PyVertical, a framework supporting vertical federated learning using split neural networks. The proposed framework allows a data scientist to train neural networks on data features vertically partitioned across multiple owners while keeping raw data on an owner's device. To link entities shared across different datasets' partitions, we use Private Set Intersection on IDs associated with data points. To demonstrate the validity of the proposed framework, we present the training of a simple dual-headed split neural network for a MNIST classification task, with data samples verticall"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.00489","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/2104.00489/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":"2026-07-05T02:32:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T65ybTjy9SUqMyG15nNDgtdq5WpPHcFtkchqBmQfdQseQOGkCMwolXKwgK6+UlRxAxJzI9Sh3+KwLEE8/xlyBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:12:24.508883Z"},"content_sha256":"bda90c1a36098e65c6842205baab85918ad729147607fb981582c44aababfaf4","schema_version":"1.0","event_id":"sha256:bda90c1a36098e65c6842205baab85918ad729147607fb981582c44aababfaf4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CSBNAV3TAZHBE5MWX3VJCEM6IO/bundle.json","state_url":"https://pith.science/pith/CSBNAV3TAZHBE5MWX3VJCEM6IO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CSBNAV3TAZHBE5MWX3VJCEM6IO/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":"2026-07-07T05:12:24Z","links":{"resolver":"https://pith.science/pith/CSBNAV3TAZHBE5MWX3VJCEM6IO","bundle":"https://pith.science/pith/CSBNAV3TAZHBE5MWX3VJCEM6IO/bundle.json","state":"https://pith.science/pith/CSBNAV3TAZHBE5MWX3VJCEM6IO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CSBNAV3TAZHBE5MWX3VJCEM6IO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:CSBNAV3TAZHBE5MWX3VJCEM6IO","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":"4783e487867cdc41188a21a3f624fc43e18095e3a9347c33b94fc84e844e6f43","cross_cats_sorted":["cs.CR","cs.DC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-04-01T14:21:33Z","title_canon_sha256":"385bff89fe34006cdbe681cbe147af1d04e71293f82f8cb60f89d7eb0d19d29b"},"schema_version":"1.0","source":{"id":"2104.00489","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.00489","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"arxiv_version","alias_value":"2104.00489v3","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.00489","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"pith_short_12","alias_value":"CSBNAV3TAZHB","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"pith_short_16","alias_value":"CSBNAV3TAZHBE5MW","created_at":"2026-07-05T02:32:04Z"},{"alias_kind":"pith_short_8","alias_value":"CSBNAV3T","created_at":"2026-07-05T02:32:04Z"}],"graph_snapshots":[{"event_id":"sha256:bda90c1a36098e65c6842205baab85918ad729147607fb981582c44aababfaf4","target":"graph","created_at":"2026-07-05T02:32:04Z","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/2104.00489/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce PyVertical, a framework supporting vertical federated learning using split neural networks. The proposed framework allows a data scientist to train neural networks on data features vertically partitioned across multiple owners while keeping raw data on an owner's device. To link entities shared across different datasets' partitions, we use Private Set Intersection on IDs associated with data points. To demonstrate the validity of the proposed framework, we present the training of a simple dual-headed split neural network for a MNIST classification task, with data samples verticall","authors_text":"Abbas Ismail, Adam James Hall, Daniele Romanini, Michael A. Hoeh, Pavlos Papadopoulos, Robert Sandmann, Robin Roehm, Tom Titcombe, Tudor Cebere","cross_cats":["cs.CR","cs.DC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-04-01T14:21:33Z","title":"PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.00489","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":"sha256:92f8eaa622ecaa76d8a7ad418ec46f477a34cb69ecd8d074b530a8ae457bb63a","target":"record","created_at":"2026-07-05T02:32:04Z","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":"4783e487867cdc41188a21a3f624fc43e18095e3a9347c33b94fc84e844e6f43","cross_cats_sorted":["cs.CR","cs.DC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-04-01T14:21:33Z","title_canon_sha256":"385bff89fe34006cdbe681cbe147af1d04e71293f82f8cb60f89d7eb0d19d29b"},"schema_version":"1.0","source":{"id":"2104.00489","kind":"arxiv","version":3}},"canonical_sha256":"1482d05773064e127596beea91119e43a9f5b9bc8233257fc4ed621ac200c460","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1482d05773064e127596beea91119e43a9f5b9bc8233257fc4ed621ac200c460","first_computed_at":"2026-07-05T02:32:04.865665Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:32:04.865665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8Ts1A+JttabX56Vc2NnsVlcbvWdNYDq5Ez5AWqQ2lNnFaZ98pWj8zkxkt6OSyLAfHrg0YpBiOPbMDTEBPROPCA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:32:04.866061Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.00489","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:92f8eaa622ecaa76d8a7ad418ec46f477a34cb69ecd8d074b530a8ae457bb63a","sha256:bda90c1a36098e65c6842205baab85918ad729147607fb981582c44aababfaf4"],"state_sha256":"dee41dc2ed32591c5c10a5f62c51d4a267231e2dad656790bcb2737b5113aaff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q1sIIg941pAjXTPsV5dmcXhYAjIw1KqBUBmmYAo2YWDfhrwuVCeF1LC6Mbq0zIePCEAflVb7wy9H7MZoAn/OCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T05:12:24.512835Z","bundle_sha256":"22affd0864f42b5ee4104286529e66ec77cd08c2e8fd9b36198107827de9b0a8"}}