{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:N4QNFQ6L7CNTHI655MYEQGZVMB","short_pith_number":"pith:N4QNFQ6L","canonical_record":{"source":{"id":"2402.09059","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-14T10:15:43Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"59ddb7779f0fb5880cc50d8dd9aab470e81ae8f9d32aae841a92752db5ea7e70","abstract_canon_sha256":"3c5dbd493555f18f6f436a9af43d789936a44f0c4d2c07adc56d3afc88d91bc5"},"schema_version":"1.0"},"canonical_sha256":"6f20d2c3cbf89b33a3ddeb30481b35606ef2c481f9273c55b69187dde10b331a","source":{"kind":"arxiv","id":"2402.09059","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.09059","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"arxiv_version","alias_value":"2402.09059v1","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.09059","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"pith_short_12","alias_value":"N4QNFQ6L7CNT","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"pith_short_16","alias_value":"N4QNFQ6L7CNTHI65","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"pith_short_8","alias_value":"N4QNFQ6L","created_at":"2026-07-05T07:45:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:N4QNFQ6L7CNTHI655MYEQGZVMB","target":"record","payload":{"canonical_record":{"source":{"id":"2402.09059","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-14T10:15:43Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"59ddb7779f0fb5880cc50d8dd9aab470e81ae8f9d32aae841a92752db5ea7e70","abstract_canon_sha256":"3c5dbd493555f18f6f436a9af43d789936a44f0c4d2c07adc56d3afc88d91bc5"},"schema_version":"1.0"},"canonical_sha256":"6f20d2c3cbf89b33a3ddeb30481b35606ef2c481f9273c55b69187dde10b331a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:45:07.954631Z","signature_b64":"VtEmBAVtw3vdHVsx5B8EpWKA25nH9Mc3DWkf/sBN3EGPYN1/s6c4OJCiN/3fupBZ+oSntVWHOkjW+2pG9aBkAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f20d2c3cbf89b33a3ddeb30481b35606ef2c481f9273c55b69187dde10b331a","last_reissued_at":"2026-07-05T07:45:07.954213Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:45:07.954213Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.09059","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:45:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b4BMpg6wQ6kBhPBYtixgwF8Snv2EaycJJnuraZd7j52TrpTMc8A259VkE/0E1U/Gjx3Tit3Tv9YDf/h0Eyz0Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:23:59.153500Z"},"content_sha256":"9943e9354ff73e5b70be48ff2766641de9178590af80282ee07518214d84a737","schema_version":"1.0","event_id":"sha256:9943e9354ff73e5b70be48ff2766641de9178590af80282ee07518214d84a737"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:N4QNFQ6L7CNTHI655MYEQGZVMB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"I can't see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.LG","authors_text":"Daniel Takabi, Prajwal Panzade, Zhipeng Cai","submitted_at":"2024-02-14T10:15:43Z","abstract_excerpt":"In today's machine learning landscape, fine-tuning pretrained transformer models has emerged as an essential technique, particularly in scenarios where access to task-aligned training data is limited. However, challenges surface when data sharing encounters obstacles due to stringent privacy regulations or user apprehension regarding personal information disclosure. Earlier works based on secure multiparty computation (SMC) and fully homomorphic encryption (FHE) for privacy-preserving machine learning (PPML) focused more on privacy-preserving inference than privacy-preserving training. In resp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.09059","kind":"arxiv","version":1},"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/2402.09059/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":"2026-07-05T07:45:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6QRleJTYHjpVr+w0AwSb3nGFcbnZJXAJgYfF8XfEFsP+o6q8Oq7cW943LySJT5WnX2ivb4zhdYrqS3IFIZiEAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:23:59.153932Z"},"content_sha256":"be596fef32ac20b57eb582bee39e97a43991f696058dc310b45c884f4380386d","schema_version":"1.0","event_id":"sha256:be596fef32ac20b57eb582bee39e97a43991f696058dc310b45c884f4380386d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N4QNFQ6L7CNTHI655MYEQGZVMB/bundle.json","state_url":"https://pith.science/pith/N4QNFQ6L7CNTHI655MYEQGZVMB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N4QNFQ6L7CNTHI655MYEQGZVMB/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":"2026-08-18T07:23:59Z","links":{"resolver":"https://pith.science/pith/N4QNFQ6L7CNTHI655MYEQGZVMB","bundle":"https://pith.science/pith/N4QNFQ6L7CNTHI655MYEQGZVMB/bundle.json","state":"https://pith.science/pith/N4QNFQ6L7CNTHI655MYEQGZVMB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N4QNFQ6L7CNTHI655MYEQGZVMB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:N4QNFQ6L7CNTHI655MYEQGZVMB","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":"3c5dbd493555f18f6f436a9af43d789936a44f0c4d2c07adc56d3afc88d91bc5","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-14T10:15:43Z","title_canon_sha256":"59ddb7779f0fb5880cc50d8dd9aab470e81ae8f9d32aae841a92752db5ea7e70"},"schema_version":"1.0","source":{"id":"2402.09059","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.09059","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"arxiv_version","alias_value":"2402.09059v1","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.09059","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"pith_short_12","alias_value":"N4QNFQ6L7CNT","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"pith_short_16","alias_value":"N4QNFQ6L7CNTHI65","created_at":"2026-07-05T07:45:07Z"},{"alias_kind":"pith_short_8","alias_value":"N4QNFQ6L","created_at":"2026-07-05T07:45:07Z"}],"graph_snapshots":[{"event_id":"sha256:be596fef32ac20b57eb582bee39e97a43991f696058dc310b45c884f4380386d","target":"graph","created_at":"2026-07-05T07:45:07Z","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/2402.09059/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In today's machine learning landscape, fine-tuning pretrained transformer models has emerged as an essential technique, particularly in scenarios where access to task-aligned training data is limited. However, challenges surface when data sharing encounters obstacles due to stringent privacy regulations or user apprehension regarding personal information disclosure. Earlier works based on secure multiparty computation (SMC) and fully homomorphic encryption (FHE) for privacy-preserving machine learning (PPML) focused more on privacy-preserving inference than privacy-preserving training. In resp","authors_text":"Daniel Takabi, Prajwal Panzade, Zhipeng Cai","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-14T10:15:43Z","title":"I can't see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.09059","kind":"arxiv","version":1},"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":"sha256:9943e9354ff73e5b70be48ff2766641de9178590af80282ee07518214d84a737","target":"record","created_at":"2026-07-05T07:45:07Z","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":"3c5dbd493555f18f6f436a9af43d789936a44f0c4d2c07adc56d3afc88d91bc5","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-14T10:15:43Z","title_canon_sha256":"59ddb7779f0fb5880cc50d8dd9aab470e81ae8f9d32aae841a92752db5ea7e70"},"schema_version":"1.0","source":{"id":"2402.09059","kind":"arxiv","version":1}},"canonical_sha256":"6f20d2c3cbf89b33a3ddeb30481b35606ef2c481f9273c55b69187dde10b331a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6f20d2c3cbf89b33a3ddeb30481b35606ef2c481f9273c55b69187dde10b331a","first_computed_at":"2026-07-05T07:45:07.954213Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:45:07.954213Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VtEmBAVtw3vdHVsx5B8EpWKA25nH9Mc3DWkf/sBN3EGPYN1/s6c4OJCiN/3fupBZ+oSntVWHOkjW+2pG9aBkAw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:45:07.954631Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.09059","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9943e9354ff73e5b70be48ff2766641de9178590af80282ee07518214d84a737","sha256:be596fef32ac20b57eb582bee39e97a43991f696058dc310b45c884f4380386d"],"state_sha256":"fa84f36c40f48f0adf9a4d64d7711eb1bc4cf2867e8548ab1bc14022d1b38ade"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9k/MP/KWt0DyILdoV0VVfoWiafXTIDfF/eyvBgGF/7vKuV+e57P/agCmLFxjdEkzflSAt3VtVU6KNG6VngRHBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T07:23:59.156270Z","bundle_sha256":"5c6122d2cf47c7bd303f49148e16810b348ca8a0229b0d4361fee63d5eb9b635"}}