{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:6RBLHNLYFOXXMI5AYBWO4XA2AU","short_pith_number":"pith:6RBLHNLY","canonical_record":{"source":{"id":"2411.02669","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-04T23:07:51Z","cross_cats_sorted":[],"title_canon_sha256":"9cd69a961b087cad503ff0d1c92f099dc1699aa4574a7af50fbba879b2a93045","abstract_canon_sha256":"25c43be595a02c9605626e3045bbdf694d1780af52301e4e08ed3a9dbbad9396"},"schema_version":"1.0"},"canonical_sha256":"f442b3b5782baf7623a0c06cee5c1a05153d109bc30cc7a26fe79417844b63cb","source":{"kind":"arxiv","id":"2411.02669","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02669","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02669v1","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02669","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"pith_short_12","alias_value":"6RBLHNLYFOXX","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"6RBLHNLYFOXXMI5A","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"6RBLHNLY","created_at":"2026-07-05T09:31:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:6RBLHNLYFOXXMI5AYBWO4XA2AU","target":"record","payload":{"canonical_record":{"source":{"id":"2411.02669","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-04T23:07:51Z","cross_cats_sorted":[],"title_canon_sha256":"9cd69a961b087cad503ff0d1c92f099dc1699aa4574a7af50fbba879b2a93045","abstract_canon_sha256":"25c43be595a02c9605626e3045bbdf694d1780af52301e4e08ed3a9dbbad9396"},"schema_version":"1.0"},"canonical_sha256":"f442b3b5782baf7623a0c06cee5c1a05153d109bc30cc7a26fe79417844b63cb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:31:15.838019Z","signature_b64":"s+qnBkO6u+l2QuKW8UAgaCyA8XVLD33SWlH45G/uDWqlH5WrBMOQIS0ttaXZ9uQ/YjVdLlmHCyMXayAymRFsDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f442b3b5782baf7623a0c06cee5c1a05153d109bc30cc7a26fe79417844b63cb","last_reissued_at":"2026-07-05T09:31:15.836906Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:31:15.836906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.02669","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":"2026-07-05T09:31:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xmIXa2gkcu90xdVM00ZyjqJX6FGQrIzJ0Q1etEZc8qw1nU6xzvWkYwD0g/vr2rzXi3if11RR4bo4lKrTlxmICg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:09:03.933580Z"},"content_sha256":"d8467368d8308d77540798df2370a3be5ef42263a25cd38ecee0bb74c873e4a1","schema_version":"1.0","event_id":"sha256:d8467368d8308d77540798df2370a3be5ef42263a25cd38ecee0bb74c873e4a1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:6RBLHNLYFOXXMI5AYBWO4XA2AU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ivor Tsang Fellow, Ke Ma, Qing Guo, Sensen Gao, Simeng Qin, Xiaochun Cao, Xiaojun Jia, Yang Liu, Yihao Huang","submitted_at":"2024-11-04T23:07:51Z","abstract_excerpt":"Vision-language pre-training (VLP) models excel at interpreting both images and text but remain vulnerable to multimodal adversarial examples (AEs). Advancing the generation of transferable AEs, which succeed across unseen models, is key to developing more robust and practical VLP models. Previous approaches augment image-text pairs to enhance diversity within the adversarial example generation process, aiming to improve transferability by expanding the contrast space of image-text features. However, these methods focus solely on diversity around the current AEs, yielding limited gains in tran"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02669","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/2411.02669/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":"2026-07-05T09:31:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MgUiygQrD2CnAsQx4EuS0xXmCkryRRq7BmYMX6lnz0BbJ+cHvKfOMWOXNBSFjk588l34TALe1qnhfDLLbXxUCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:09:03.934202Z"},"content_sha256":"917c9ef11d3551755e0c5923cbd02c48cd3c49495947c60676190fcf78819491","schema_version":"1.0","event_id":"sha256:917c9ef11d3551755e0c5923cbd02c48cd3c49495947c60676190fcf78819491"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6RBLHNLYFOXXMI5AYBWO4XA2AU/bundle.json","state_url":"https://pith.science/pith/6RBLHNLYFOXXMI5AYBWO4XA2AU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6RBLHNLYFOXXMI5AYBWO4XA2AU/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":"2026-08-23T04:09:03Z","links":{"resolver":"https://pith.science/pith/6RBLHNLYFOXXMI5AYBWO4XA2AU","bundle":"https://pith.science/pith/6RBLHNLYFOXXMI5AYBWO4XA2AU/bundle.json","state":"https://pith.science/pith/6RBLHNLYFOXXMI5AYBWO4XA2AU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6RBLHNLYFOXXMI5AYBWO4XA2AU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6RBLHNLYFOXXMI5AYBWO4XA2AU","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":"25c43be595a02c9605626e3045bbdf694d1780af52301e4e08ed3a9dbbad9396","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-04T23:07:51Z","title_canon_sha256":"9cd69a961b087cad503ff0d1c92f099dc1699aa4574a7af50fbba879b2a93045"},"schema_version":"1.0","source":{"id":"2411.02669","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02669","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02669v1","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02669","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"pith_short_12","alias_value":"6RBLHNLYFOXX","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"6RBLHNLYFOXXMI5A","created_at":"2026-07-05T09:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"6RBLHNLY","created_at":"2026-07-05T09:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:917c9ef11d3551755e0c5923cbd02c48cd3c49495947c60676190fcf78819491","target":"graph","created_at":"2026-07-05T09:31:15Z","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/2411.02669/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-language pre-training (VLP) models excel at interpreting both images and text but remain vulnerable to multimodal adversarial examples (AEs). Advancing the generation of transferable AEs, which succeed across unseen models, is key to developing more robust and practical VLP models. Previous approaches augment image-text pairs to enhance diversity within the adversarial example generation process, aiming to improve transferability by expanding the contrast space of image-text features. However, these methods focus solely on diversity around the current AEs, yielding limited gains in tran","authors_text":"Ivor Tsang Fellow, Ke Ma, Qing Guo, Sensen Gao, Simeng Qin, Xiaochun Cao, Xiaojun Jia, Yang Liu, Yihao Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-04T23:07:51Z","title":"Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02669","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:d8467368d8308d77540798df2370a3be5ef42263a25cd38ecee0bb74c873e4a1","target":"record","created_at":"2026-07-05T09:31:15Z","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":"25c43be595a02c9605626e3045bbdf694d1780af52301e4e08ed3a9dbbad9396","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-04T23:07:51Z","title_canon_sha256":"9cd69a961b087cad503ff0d1c92f099dc1699aa4574a7af50fbba879b2a93045"},"schema_version":"1.0","source":{"id":"2411.02669","kind":"arxiv","version":1}},"canonical_sha256":"f442b3b5782baf7623a0c06cee5c1a05153d109bc30cc7a26fe79417844b63cb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f442b3b5782baf7623a0c06cee5c1a05153d109bc30cc7a26fe79417844b63cb","first_computed_at":"2026-07-05T09:31:15.836906Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:31:15.836906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s+qnBkO6u+l2QuKW8UAgaCyA8XVLD33SWlH45G/uDWqlH5WrBMOQIS0ttaXZ9uQ/YjVdLlmHCyMXayAymRFsDA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:31:15.838019Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.02669","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8467368d8308d77540798df2370a3be5ef42263a25cd38ecee0bb74c873e4a1","sha256:917c9ef11d3551755e0c5923cbd02c48cd3c49495947c60676190fcf78819491"],"state_sha256":"6a60341a8b4dfe3da4c97bbabd1f9bb46a23be360b2fd3e554f4da3aa43001b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"if7NXTh9a4hPrmmGyMN4SoCHAX+gCXwaP+fROZCo2pa3Aq8asg5SdSJ+kx0aT8BIDC0bBD0RxvXnuA+lPhVwAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T04:09:03.941780Z","bundle_sha256":"459276770c199b6e0f6dd58f7471ab5e38f9b9cdc77674692163b966f18942b1"}}