{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:V53WUQS3WFNNR7GYBOIHIV7WVY","short_pith_number":"pith:V53WUQS3","canonical_record":{"source":{"id":"2409.15361","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-18T08:04:24Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"aa2eb8814c3e3e8f024a7d2904813d238c3f925659b4329cf1616eeb93eeb244","abstract_canon_sha256":"af17e45b107a0084007b5a4201780eedec87f5892f0101f6bacd54d4078eddcb"},"schema_version":"1.0"},"canonical_sha256":"af776a425bb15ad8fcd80b907457f6ae3a8bed1dba6b1c7fb5bb127763e5e53f","source":{"kind":"arxiv","id":"2409.15361","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.15361","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"arxiv_version","alias_value":"2409.15361v1","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.15361","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"pith_short_12","alias_value":"V53WUQS3WFNN","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"pith_short_16","alias_value":"V53WUQS3WFNNR7GY","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"pith_short_8","alias_value":"V53WUQS3","created_at":"2026-07-05T09:10:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:V53WUQS3WFNNR7GYBOIHIV7WVY","target":"record","payload":{"canonical_record":{"source":{"id":"2409.15361","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-18T08:04:24Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"aa2eb8814c3e3e8f024a7d2904813d238c3f925659b4329cf1616eeb93eeb244","abstract_canon_sha256":"af17e45b107a0084007b5a4201780eedec87f5892f0101f6bacd54d4078eddcb"},"schema_version":"1.0"},"canonical_sha256":"af776a425bb15ad8fcd80b907457f6ae3a8bed1dba6b1c7fb5bb127763e5e53f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:10:53.771605Z","signature_b64":"fI9hxHCLSguO/lXa2s6o18A0zQJ07dsjJ5LD5s0gZZYTDWPYprPCZY5wZazreNhpGygOmSMt51/+tcOiRcVRCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af776a425bb15ad8fcd80b907457f6ae3a8bed1dba6b1c7fb5bb127763e5e53f","last_reissued_at":"2026-07-05T09:10:53.771177Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:10:53.771177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.15361","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":"2026-07-05T09:10:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"855c2Ku2Jk2adwWXvexDRAsDxSCXHCI8yyBsGrx4Lv6fCxjW8AXnZ0TK2VgtNPbG1+hRFpTqUGKLXMW1cQiTBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:28:41.997641Z"},"content_sha256":"9554ff8d28b8c430b59b8d22cb06aa2730822573639be76e2fe6d3c27e307b44","schema_version":"1.0","event_id":"sha256:9554ff8d28b8c430b59b8d22cb06aa2730822573639be76e2fe6d3c27e307b44"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:V53WUQS3WFNNR7GYBOIHIV7WVY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multitask Mayhem: Unveiling and Mitigating Safety Gaps in LLMs Fine-tuning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Essa Jan, Faizan Ahmad, Fareed Zaffar, Moiz Ali, Nouar AlDahoul, Yasir Zaki","submitted_at":"2024-09-18T08:04:24Z","abstract_excerpt":"Recent breakthroughs in Large Language Models (LLMs) have led to their adoption across a wide range of tasks, ranging from code generation to machine translation and sentiment analysis, etc. Red teaming/Safety alignment efforts show that fine-tuning models on benign (non-harmful) data could compromise safety. However, it remains unclear to what extent this phenomenon is influenced by different variables, including fine-tuning task, model calibrations, etc. This paper explores the task-wise safety degradation due to fine-tuning on downstream tasks such as summarization, code generation, transla"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.15361","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/2409.15361/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":"2026-07-05T09:10:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B7C8BaElWpFCVLmvB4WKT7shw/P81dv2qAjQh0lzpuQAr5IJqBHrMe5fsB/Abg8zTbvKX0q9gPzb64fxbpWRCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:28:41.998172Z"},"content_sha256":"a7520046ab354d2f53e1c0c53dea6891a9455d4a4f2e77866039ba99fa4454fb","schema_version":"1.0","event_id":"sha256:a7520046ab354d2f53e1c0c53dea6891a9455d4a4f2e77866039ba99fa4454fb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V53WUQS3WFNNR7GYBOIHIV7WVY/bundle.json","state_url":"https://pith.science/pith/V53WUQS3WFNNR7GYBOIHIV7WVY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V53WUQS3WFNNR7GYBOIHIV7WVY/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":"2026-08-09T07:28:42Z","links":{"resolver":"https://pith.science/pith/V53WUQS3WFNNR7GYBOIHIV7WVY","bundle":"https://pith.science/pith/V53WUQS3WFNNR7GYBOIHIV7WVY/bundle.json","state":"https://pith.science/pith/V53WUQS3WFNNR7GYBOIHIV7WVY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V53WUQS3WFNNR7GYBOIHIV7WVY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:V53WUQS3WFNNR7GYBOIHIV7WVY","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":"af17e45b107a0084007b5a4201780eedec87f5892f0101f6bacd54d4078eddcb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-18T08:04:24Z","title_canon_sha256":"aa2eb8814c3e3e8f024a7d2904813d238c3f925659b4329cf1616eeb93eeb244"},"schema_version":"1.0","source":{"id":"2409.15361","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.15361","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"arxiv_version","alias_value":"2409.15361v1","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.15361","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"pith_short_12","alias_value":"V53WUQS3WFNN","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"pith_short_16","alias_value":"V53WUQS3WFNNR7GY","created_at":"2026-07-05T09:10:53Z"},{"alias_kind":"pith_short_8","alias_value":"V53WUQS3","created_at":"2026-07-05T09:10:53Z"}],"graph_snapshots":[{"event_id":"sha256:a7520046ab354d2f53e1c0c53dea6891a9455d4a4f2e77866039ba99fa4454fb","target":"graph","created_at":"2026-07-05T09:10:53Z","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/2409.15361/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent breakthroughs in Large Language Models (LLMs) have led to their adoption across a wide range of tasks, ranging from code generation to machine translation and sentiment analysis, etc. Red teaming/Safety alignment efforts show that fine-tuning models on benign (non-harmful) data could compromise safety. However, it remains unclear to what extent this phenomenon is influenced by different variables, including fine-tuning task, model calibrations, etc. This paper explores the task-wise safety degradation due to fine-tuning on downstream tasks such as summarization, code generation, transla","authors_text":"Essa Jan, Faizan Ahmad, Fareed Zaffar, Moiz Ali, Nouar AlDahoul, Yasir Zaki","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-18T08:04:24Z","title":"Multitask Mayhem: Unveiling and Mitigating Safety Gaps in LLMs Fine-tuning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.15361","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":"sha256:9554ff8d28b8c430b59b8d22cb06aa2730822573639be76e2fe6d3c27e307b44","target":"record","created_at":"2026-07-05T09:10:53Z","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":"af17e45b107a0084007b5a4201780eedec87f5892f0101f6bacd54d4078eddcb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-18T08:04:24Z","title_canon_sha256":"aa2eb8814c3e3e8f024a7d2904813d238c3f925659b4329cf1616eeb93eeb244"},"schema_version":"1.0","source":{"id":"2409.15361","kind":"arxiv","version":1}},"canonical_sha256":"af776a425bb15ad8fcd80b907457f6ae3a8bed1dba6b1c7fb5bb127763e5e53f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af776a425bb15ad8fcd80b907457f6ae3a8bed1dba6b1c7fb5bb127763e5e53f","first_computed_at":"2026-07-05T09:10:53.771177Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:10:53.771177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fI9hxHCLSguO/lXa2s6o18A0zQJ07dsjJ5LD5s0gZZYTDWPYprPCZY5wZazreNhpGygOmSMt51/+tcOiRcVRCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:10:53.771605Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.15361","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9554ff8d28b8c430b59b8d22cb06aa2730822573639be76e2fe6d3c27e307b44","sha256:a7520046ab354d2f53e1c0c53dea6891a9455d4a4f2e77866039ba99fa4454fb"],"state_sha256":"0b32caea94cdea3ffa21410ef84073fc21a179ea659a5eed97cfe39ec9e75643"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1KLZy6+E2un9famzni8+0sZ10KO1OHZY32t5ONGK/WRib58jOy8Cn9YN6PBW0HeYouaAsVfQ515GJvTLHUygBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T07:28:42.003772Z","bundle_sha256":"386ca69d03303bf734976141a7ae82a5614c660dc3fb2630440e4e5e63fa4657"}}