{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:Q6N6EZVEGYDVEURNG6EBG3IIHI","short_pith_number":"pith:Q6N6EZVE","canonical_record":{"source":{"id":"2407.12281","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-17T03:02:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"32096b0d4051a74be0dca8da851bbd6661f0f36d8c47c08eb9065c21fd282991","abstract_canon_sha256":"a775650ca5366d3dc79c6315379b2bec158315abf9475e2807ea8e8ebd5f55d5"},"schema_version":"1.0"},"canonical_sha256":"879be266a4360752522d3788136d083a350c91949d5837b6309e12aa9b336f76","source":{"kind":"arxiv","id":"2407.12281","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.12281","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"arxiv_version","alias_value":"2407.12281v2","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.12281","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"pith_short_12","alias_value":"Q6N6EZVEGYDV","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"pith_short_16","alias_value":"Q6N6EZVEGYDVEURN","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"pith_short_8","alias_value":"Q6N6EZVE","created_at":"2026-07-05T08:45:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:Q6N6EZVEGYDVEURNG6EBG3IIHI","target":"record","payload":{"canonical_record":{"source":{"id":"2407.12281","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-17T03:02:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"32096b0d4051a74be0dca8da851bbd6661f0f36d8c47c08eb9065c21fd282991","abstract_canon_sha256":"a775650ca5366d3dc79c6315379b2bec158315abf9475e2807ea8e8ebd5f55d5"},"schema_version":"1.0"},"canonical_sha256":"879be266a4360752522d3788136d083a350c91949d5837b6309e12aa9b336f76","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:45:31.313372Z","signature_b64":"iyo6YalHMnmd1bOxuLr+4J0PVcPvrr4rl9/FnKSkJGsSHNm9BMP7//D5n5vVgijJqIPy0pKdoloI4QlyqxQwAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"879be266a4360752522d3788136d083a350c91949d5837b6309e12aa9b336f76","last_reissued_at":"2026-07-05T08:45:31.312949Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:45:31.312949Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.12281","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":"2026-07-05T08:45:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EcloVVigq+39uaSUR87ruj5eGyE9IZRmkvj4r1i/01EUnLu2QAktmD7mp8IXDi/JAM/8q/EWpw+OusfI56GUCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T00:46:34.571013Z"},"content_sha256":"56f72d37a8c307a6b2200208a56addc137c897dea3a789113cc7fbbb2d31c1af","schema_version":"1.0","event_id":"sha256:56f72d37a8c307a6b2200208a56addc137c897dea3a789113cc7fbbb2d31c1af"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:Q6N6EZVEGYDVEURNG6EBG3IIHI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Turning Generative Models Degenerate: The Power of Data Poisoning Attacks","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CR","authors_text":"Farhan Ahmed, Ling Cai, Nathalie Baracaldo, Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou","submitted_at":"2024-07-17T03:02:15Z","abstract_excerpt":"The increasing use of large language models (LLMs) trained by third parties raises significant security concerns. In particular, malicious actors can introduce backdoors through poisoning attacks to generate undesirable outputs. While such attacks have been extensively studied in image domains and classification tasks, they remain underexplored for natural language generation (NLG) tasks. To address this gap, we conduct an investigation of various poisoning techniques targeting the LLM's fine-tuning phase via prefix-tuning, a Parameter Efficient Fine-Tuning (PEFT) method. We assess their effec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.12281","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/2407.12281/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":"2026-07-05T08:45:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y2tI+rth6LLa36uv5dD+k52DL5I9df+i5vMnCnghvl4kuFVmxYdnUhZisbB3AAH5dAuAb0W2+/VAo7WBjW0NDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T00:46:34.571535Z"},"content_sha256":"342d88622a6d457fa3cf80c3c74ea9991b52cb32146e7b49603df3da117a2efc","schema_version":"1.0","event_id":"sha256:342d88622a6d457fa3cf80c3c74ea9991b52cb32146e7b49603df3da117a2efc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q6N6EZVEGYDVEURNG6EBG3IIHI/bundle.json","state_url":"https://pith.science/pith/Q6N6EZVEGYDVEURNG6EBG3IIHI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q6N6EZVEGYDVEURNG6EBG3IIHI/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":"2026-08-11T00:46:34Z","links":{"resolver":"https://pith.science/pith/Q6N6EZVEGYDVEURNG6EBG3IIHI","bundle":"https://pith.science/pith/Q6N6EZVEGYDVEURNG6EBG3IIHI/bundle.json","state":"https://pith.science/pith/Q6N6EZVEGYDVEURNG6EBG3IIHI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q6N6EZVEGYDVEURNG6EBG3IIHI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:Q6N6EZVEGYDVEURNG6EBG3IIHI","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":"a775650ca5366d3dc79c6315379b2bec158315abf9475e2807ea8e8ebd5f55d5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-17T03:02:15Z","title_canon_sha256":"32096b0d4051a74be0dca8da851bbd6661f0f36d8c47c08eb9065c21fd282991"},"schema_version":"1.0","source":{"id":"2407.12281","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.12281","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"arxiv_version","alias_value":"2407.12281v2","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.12281","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"pith_short_12","alias_value":"Q6N6EZVEGYDV","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"pith_short_16","alias_value":"Q6N6EZVEGYDVEURN","created_at":"2026-07-05T08:45:31Z"},{"alias_kind":"pith_short_8","alias_value":"Q6N6EZVE","created_at":"2026-07-05T08:45:31Z"}],"graph_snapshots":[{"event_id":"sha256:342d88622a6d457fa3cf80c3c74ea9991b52cb32146e7b49603df3da117a2efc","target":"graph","created_at":"2026-07-05T08:45:31Z","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/2407.12281/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The increasing use of large language models (LLMs) trained by third parties raises significant security concerns. In particular, malicious actors can introduce backdoors through poisoning attacks to generate undesirable outputs. While such attacks have been extensively studied in image domains and classification tasks, they remain underexplored for natural language generation (NLG) tasks. To address this gap, we conduct an investigation of various poisoning techniques targeting the LLM's fine-tuning phase via prefix-tuning, a Parameter Efficient Fine-Tuning (PEFT) method. We assess their effec","authors_text":"Farhan Ahmed, Ling Cai, Nathalie Baracaldo, Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-17T03:02:15Z","title":"Turning Generative Models Degenerate: The Power of Data Poisoning Attacks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.12281","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":"sha256:56f72d37a8c307a6b2200208a56addc137c897dea3a789113cc7fbbb2d31c1af","target":"record","created_at":"2026-07-05T08:45:31Z","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":"a775650ca5366d3dc79c6315379b2bec158315abf9475e2807ea8e8ebd5f55d5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-17T03:02:15Z","title_canon_sha256":"32096b0d4051a74be0dca8da851bbd6661f0f36d8c47c08eb9065c21fd282991"},"schema_version":"1.0","source":{"id":"2407.12281","kind":"arxiv","version":2}},"canonical_sha256":"879be266a4360752522d3788136d083a350c91949d5837b6309e12aa9b336f76","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"879be266a4360752522d3788136d083a350c91949d5837b6309e12aa9b336f76","first_computed_at":"2026-07-05T08:45:31.312949Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:45:31.312949Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iyo6YalHMnmd1bOxuLr+4J0PVcPvrr4rl9/FnKSkJGsSHNm9BMP7//D5n5vVgijJqIPy0pKdoloI4QlyqxQwAg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:45:31.313372Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.12281","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:56f72d37a8c307a6b2200208a56addc137c897dea3a789113cc7fbbb2d31c1af","sha256:342d88622a6d457fa3cf80c3c74ea9991b52cb32146e7b49603df3da117a2efc"],"state_sha256":"70e599defa1cbd6df191cfd0050d8a35c1e6aa5b57670ba3808a2d76b905037b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C6z9z39XgLeIaeCFyVQ+At0/wvJtQBDTePBYcvJI1jaHBU1Aoza3+nAT8AHliACa0yscA8HVDFORtxC1AtbcCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T00:46:34.575903Z","bundle_sha256":"6ecdee5392ab79095d7dceacc9d0c9524c1f255ef13bae063cb4b45796467a7b"}}