{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:2U3XTXDRWS6L5XNQ2QRD6EYE7F","short_pith_number":"pith:2U3XTXDR","canonical_record":{"source":{"id":"2607.06913","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-07-08T02:04:47Z","cross_cats_sorted":[],"title_canon_sha256":"5c048bb6101b7eab1edfb13ca15e4a027b9dde60e45ba6d9616dd85380dbd204","abstract_canon_sha256":"84077e74913cdab591c098b18f35f91cedda0539e9f1512639a6e670c88acfe4"},"schema_version":"1.0"},"canonical_sha256":"d53779dc71b4bcbeddb0d4223f1304f97f12931342190cef6a7bb2582e488147","source":{"kind":"arxiv","id":"2607.06913","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.06913","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"arxiv_version","alias_value":"2607.06913v1","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06913","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"pith_short_12","alias_value":"2U3XTXDRWS6L","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"pith_short_16","alias_value":"2U3XTXDRWS6L5XNQ","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"pith_short_8","alias_value":"2U3XTXDR","created_at":"2026-07-09T00:19:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:2U3XTXDRWS6L5XNQ2QRD6EYE7F","target":"record","payload":{"canonical_record":{"source":{"id":"2607.06913","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-07-08T02:04:47Z","cross_cats_sorted":[],"title_canon_sha256":"5c048bb6101b7eab1edfb13ca15e4a027b9dde60e45ba6d9616dd85380dbd204","abstract_canon_sha256":"84077e74913cdab591c098b18f35f91cedda0539e9f1512639a6e670c88acfe4"},"schema_version":"1.0"},"canonical_sha256":"d53779dc71b4bcbeddb0d4223f1304f97f12931342190cef6a7bb2582e488147","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-09T00:19:39.354940Z","signature_b64":"f6nyp44OOhcmRWk0QCSOE7zt7tZhqwhq6U7OrSyou6DaporWnszywVL1u+SoDLpu3ZErQlAtN+AP0tJTwbmnCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d53779dc71b4bcbeddb0d4223f1304f97f12931342190cef6a7bb2582e488147","last_reissued_at":"2026-07-09T00:19:39.354379Z","signature_status":"signed_v1","first_computed_at":"2026-07-09T00:19:39.354379Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.06913","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":"2026-07-09T00:19:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7JGPiMo26B51kj3ABpFSkm7HH6+6Z4Uae4xpYMxRs1ljX6STbTVtSQgnB5pqrcN4ncK3i6/u5jlzQef6rSUWAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:57:22.767992Z"},"content_sha256":"620555c4117a1330557bf62a7d4ad305ed18bcfbef26731faf15555e9cf7bc2f","schema_version":"1.0","event_id":"sha256:620555c4117a1330557bf62a7d4ad305ed18bcfbef26731faf15555e9cf7bc2f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:2U3XTXDRWS6L5XNQ2QRD6EYE7F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluating LLM Robustness Under Domain-Specific Prompt Perturbations in Public Health Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CY","authors_text":"Chuqing Zhao, Haochen Yang","submitted_at":"2026-07-08T02:04:47Z","abstract_excerpt":"Large language models (LLMs) are increasingly applied in public health applications, yet their robustness to non-clinical user inputs remains underexplored. We propose a domain specific robustness benchmark that evaluates LLMs under two perturbation types that commonly arise when non-clinical users interact with health AI systems: misinformation framing (MF), where prompt might be injected by false health claims, and layperson rewriting (LR), where patients describe symptoms in everyday language rather than medical terminology. Our goal is to evaluate the stability of LLMs under these perturba"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06913","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/2607.06913/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":"2026-07-09T00:19:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"94phtVcetvQDBxDx0hDuZsD034w4dP17sb0KByHkRDF467e0BLI2ZyJoPZbi5y5l/Kb7kbVRY3vxFJqu2n4XAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:57:22.768421Z"},"content_sha256":"eacd27c6a9e609d19ee2d95a0a5ee78b2391ebf33240caa87cc340098668a0c0","schema_version":"1.0","event_id":"sha256:eacd27c6a9e609d19ee2d95a0a5ee78b2391ebf33240caa87cc340098668a0c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2U3XTXDRWS6L5XNQ2QRD6EYE7F/bundle.json","state_url":"https://pith.science/pith/2U3XTXDRWS6L5XNQ2QRD6EYE7F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2U3XTXDRWS6L5XNQ2QRD6EYE7F/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":"2026-08-03T17:57:22Z","links":{"resolver":"https://pith.science/pith/2U3XTXDRWS6L5XNQ2QRD6EYE7F","bundle":"https://pith.science/pith/2U3XTXDRWS6L5XNQ2QRD6EYE7F/bundle.json","state":"https://pith.science/pith/2U3XTXDRWS6L5XNQ2QRD6EYE7F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2U3XTXDRWS6L5XNQ2QRD6EYE7F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2U3XTXDRWS6L5XNQ2QRD6EYE7F","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":"84077e74913cdab591c098b18f35f91cedda0539e9f1512639a6e670c88acfe4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-07-08T02:04:47Z","title_canon_sha256":"5c048bb6101b7eab1edfb13ca15e4a027b9dde60e45ba6d9616dd85380dbd204"},"schema_version":"1.0","source":{"id":"2607.06913","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.06913","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"arxiv_version","alias_value":"2607.06913v1","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06913","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"pith_short_12","alias_value":"2U3XTXDRWS6L","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"pith_short_16","alias_value":"2U3XTXDRWS6L5XNQ","created_at":"2026-07-09T00:19:39Z"},{"alias_kind":"pith_short_8","alias_value":"2U3XTXDR","created_at":"2026-07-09T00:19:39Z"}],"graph_snapshots":[{"event_id":"sha256:eacd27c6a9e609d19ee2d95a0a5ee78b2391ebf33240caa87cc340098668a0c0","target":"graph","created_at":"2026-07-09T00:19:39Z","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/2607.06913/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are increasingly applied in public health applications, yet their robustness to non-clinical user inputs remains underexplored. We propose a domain specific robustness benchmark that evaluates LLMs under two perturbation types that commonly arise when non-clinical users interact with health AI systems: misinformation framing (MF), where prompt might be injected by false health claims, and layperson rewriting (LR), where patients describe symptoms in everyday language rather than medical terminology. Our goal is to evaluate the stability of LLMs under these perturba","authors_text":"Chuqing Zhao, Haochen Yang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-07-08T02:04:47Z","title":"Evaluating LLM Robustness Under Domain-Specific Prompt Perturbations in Public Health Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06913","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":"sha256:620555c4117a1330557bf62a7d4ad305ed18bcfbef26731faf15555e9cf7bc2f","target":"record","created_at":"2026-07-09T00:19:39Z","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":"84077e74913cdab591c098b18f35f91cedda0539e9f1512639a6e670c88acfe4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-07-08T02:04:47Z","title_canon_sha256":"5c048bb6101b7eab1edfb13ca15e4a027b9dde60e45ba6d9616dd85380dbd204"},"schema_version":"1.0","source":{"id":"2607.06913","kind":"arxiv","version":1}},"canonical_sha256":"d53779dc71b4bcbeddb0d4223f1304f97f12931342190cef6a7bb2582e488147","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d53779dc71b4bcbeddb0d4223f1304f97f12931342190cef6a7bb2582e488147","first_computed_at":"2026-07-09T00:19:39.354379Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-09T00:19:39.354379Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"f6nyp44OOhcmRWk0QCSOE7zt7tZhqwhq6U7OrSyou6DaporWnszywVL1u+SoDLpu3ZErQlAtN+AP0tJTwbmnCg==","signature_status":"signed_v1","signed_at":"2026-07-09T00:19:39.354940Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.06913","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:620555c4117a1330557bf62a7d4ad305ed18bcfbef26731faf15555e9cf7bc2f","sha256:eacd27c6a9e609d19ee2d95a0a5ee78b2391ebf33240caa87cc340098668a0c0"],"state_sha256":"d6f0dda89d7c6246ecbf6b7dc76deeb5c47ab776357c64149228e56fb978ffee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZCMUbBTOw+J7Y2d6LKbmVwqA38JXcAYF1Mva5mQ86E5GuAEH2Fhgss27/CT21/bPEnQeE/jypnrNDmm2icprDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T17:57:22.771405Z","bundle_sha256":"77d633dfc965c5c007da8dc99aee227af70b646c2be2dd3edc2fbb88397188c8"}}