{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ZTWL4FFAGLAXSEK2OU2GRDQJJV","short_pith_number":"pith:ZTWL4FFA","canonical_record":{"source":{"id":"2403.09766","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-14T17:59:35Z","cross_cats_sorted":[],"title_canon_sha256":"657ea49bfc90d6bd7d8f39e495c8ad87ca83a88aedf876ed8799ed7bfa6257b0","abstract_canon_sha256":"ac69ede94b79214181e87b2c1a0cb003a0fae3bde61d0183012f7f554af20271"},"schema_version":"1.0"},"canonical_sha256":"ccecbe14a032c179115a7534688e094d531eaa660b26574ee641dba38fb4748b","source":{"kind":"arxiv","id":"2403.09766","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.09766","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"arxiv_version","alias_value":"2403.09766v1","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.09766","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"pith_short_12","alias_value":"ZTWL4FFAGLAX","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"pith_short_16","alias_value":"ZTWL4FFAGLAXSEK2","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"pith_short_8","alias_value":"ZTWL4FFA","created_at":"2026-07-05T07:56:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ZTWL4FFAGLAXSEK2OU2GRDQJJV","target":"record","payload":{"canonical_record":{"source":{"id":"2403.09766","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-14T17:59:35Z","cross_cats_sorted":[],"title_canon_sha256":"657ea49bfc90d6bd7d8f39e495c8ad87ca83a88aedf876ed8799ed7bfa6257b0","abstract_canon_sha256":"ac69ede94b79214181e87b2c1a0cb003a0fae3bde61d0183012f7f554af20271"},"schema_version":"1.0"},"canonical_sha256":"ccecbe14a032c179115a7534688e094d531eaa660b26574ee641dba38fb4748b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:56:24.711082Z","signature_b64":"N8ojf5VC2RV+/wV9VNM2bsEXhJMnjWY1HeUrpDUpKUM9rByKGDUEzpiD5XS+uEIe7hOP43/sjD8BWwWIGnUuCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ccecbe14a032c179115a7534688e094d531eaa660b26574ee641dba38fb4748b","last_reissued_at":"2026-07-05T07:56:24.710607Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:56:24.710607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.09766","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":"2026-07-05T07:56:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aYEWiNx+eq3BQbumbO7x71RUbca4Q/1R/8b75O3LC+48JQFOBn+sWOQRhfRGi8Zj1+sW5PlY03Z4qwTc+cksAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:05:46.872062Z"},"content_sha256":"4e626a39932a101fa721b0c4b6912f8d3446c89815cfb9e0d88cf198ec4244f9","schema_version":"1.0","event_id":"sha256:4e626a39932a101fa721b0c4b6912f8d3446c89815cfb9e0d88cf198ec4244f9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ZTWL4FFAGLAXSEK2OU2GRDQJJV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fengyuan Liu, Haochen Luo, Jindong Gu, Philip Torr","submitted_at":"2024-03-14T17:59:35Z","abstract_excerpt":"Different from traditional task-specific vision models, recent large VLMs can readily adapt to different vision tasks by simply using different textual instructions, i.e., prompts. However, a well-known concern about traditional task-specific vision models is that they can be misled by imperceptible adversarial perturbations. Furthermore, the concern is exacerbated by the phenomenon that the same adversarial perturbations can fool different task-specific models. Given that VLMs rely on prompts to adapt to different tasks, an intriguing question emerges: Can a single adversarial image mislead a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.09766","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/2403.09766/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":"2026-07-05T07:56:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"breYQiyL8kEBn7wBb/m10Ngac7SifE9v7e+Ii6iy6IF3miaui44HYKrw+JLo6DrTz/nHKOzPrqOmFslOxBW/Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:05:46.872607Z"},"content_sha256":"2732db304b2e07d8044e672a28a4950789ac9e81e0246c29979ddbad4e076654","schema_version":"1.0","event_id":"sha256:2732db304b2e07d8044e672a28a4950789ac9e81e0246c29979ddbad4e076654"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZTWL4FFAGLAXSEK2OU2GRDQJJV/bundle.json","state_url":"https://pith.science/pith/ZTWL4FFAGLAXSEK2OU2GRDQJJV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZTWL4FFAGLAXSEK2OU2GRDQJJV/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":"2026-08-06T08:05:46Z","links":{"resolver":"https://pith.science/pith/ZTWL4FFAGLAXSEK2OU2GRDQJJV","bundle":"https://pith.science/pith/ZTWL4FFAGLAXSEK2OU2GRDQJJV/bundle.json","state":"https://pith.science/pith/ZTWL4FFAGLAXSEK2OU2GRDQJJV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZTWL4FFAGLAXSEK2OU2GRDQJJV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZTWL4FFAGLAXSEK2OU2GRDQJJV","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":"ac69ede94b79214181e87b2c1a0cb003a0fae3bde61d0183012f7f554af20271","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-14T17:59:35Z","title_canon_sha256":"657ea49bfc90d6bd7d8f39e495c8ad87ca83a88aedf876ed8799ed7bfa6257b0"},"schema_version":"1.0","source":{"id":"2403.09766","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.09766","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"arxiv_version","alias_value":"2403.09766v1","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.09766","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"pith_short_12","alias_value":"ZTWL4FFAGLAX","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"pith_short_16","alias_value":"ZTWL4FFAGLAXSEK2","created_at":"2026-07-05T07:56:24Z"},{"alias_kind":"pith_short_8","alias_value":"ZTWL4FFA","created_at":"2026-07-05T07:56:24Z"}],"graph_snapshots":[{"event_id":"sha256:2732db304b2e07d8044e672a28a4950789ac9e81e0246c29979ddbad4e076654","target":"graph","created_at":"2026-07-05T07:56:24Z","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/2403.09766/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Different from traditional task-specific vision models, recent large VLMs can readily adapt to different vision tasks by simply using different textual instructions, i.e., prompts. However, a well-known concern about traditional task-specific vision models is that they can be misled by imperceptible adversarial perturbations. Furthermore, the concern is exacerbated by the phenomenon that the same adversarial perturbations can fool different task-specific models. Given that VLMs rely on prompts to adapt to different tasks, an intriguing question emerges: Can a single adversarial image mislead a","authors_text":"Fengyuan Liu, Haochen Luo, Jindong Gu, Philip Torr","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-14T17:59:35Z","title":"An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.09766","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":"sha256:4e626a39932a101fa721b0c4b6912f8d3446c89815cfb9e0d88cf198ec4244f9","target":"record","created_at":"2026-07-05T07:56:24Z","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":"ac69ede94b79214181e87b2c1a0cb003a0fae3bde61d0183012f7f554af20271","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-14T17:59:35Z","title_canon_sha256":"657ea49bfc90d6bd7d8f39e495c8ad87ca83a88aedf876ed8799ed7bfa6257b0"},"schema_version":"1.0","source":{"id":"2403.09766","kind":"arxiv","version":1}},"canonical_sha256":"ccecbe14a032c179115a7534688e094d531eaa660b26574ee641dba38fb4748b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ccecbe14a032c179115a7534688e094d531eaa660b26574ee641dba38fb4748b","first_computed_at":"2026-07-05T07:56:24.710607Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:56:24.710607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N8ojf5VC2RV+/wV9VNM2bsEXhJMnjWY1HeUrpDUpKUM9rByKGDUEzpiD5XS+uEIe7hOP43/sjD8BWwWIGnUuCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:56:24.711082Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.09766","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e626a39932a101fa721b0c4b6912f8d3446c89815cfb9e0d88cf198ec4244f9","sha256:2732db304b2e07d8044e672a28a4950789ac9e81e0246c29979ddbad4e076654"],"state_sha256":"4d2f29a2392f37b8ad89571b8060c90d61b4a5b17ebfe4530fd3572230601d75"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TiGgQB4mVX51HR0rbsRnlCN8WqcLREBvkF7CxKa1bOdZJsSUlCUJOnnixnnMkWiF8fC0V8mO8K2ry58TKjTjCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T08:05:46.877683Z","bundle_sha256":"c1cde9bafc2727437fde9c6b271ffccb2eb2db652ab33f03d6675adc01804bbf"}}