{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:5PCMPUIQZGZ35NQ5RKRTPFGX5T","short_pith_number":"pith:5PCMPUIQ","canonical_record":{"source":{"id":"2411.02902","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-05T08:35:08Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CR","cs.LG"],"title_canon_sha256":"e9891058d43567369a20961c230da8f7f2bdeb9ae026dc3402c618db74d34bb6","abstract_canon_sha256":"7db5959a3eafa181dfe45a3e06126a8cee677390b6720048aaf10c2962b96a1c"},"schema_version":"1.0"},"canonical_sha256":"ebc4c7d110c9b3beb61d8aa33794d7ece0a16816c94c044d42fa9fb14f5da44e","source":{"kind":"arxiv","id":"2411.02902","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02902","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02902v1","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02902","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"pith_short_12","alias_value":"5PCMPUIQZGZ3","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"pith_short_16","alias_value":"5PCMPUIQZGZ35NQ5","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"pith_short_8","alias_value":"5PCMPUIQ","created_at":"2026-07-05T09:31:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:5PCMPUIQZGZ35NQ5RKRTPFGX5T","target":"record","payload":{"canonical_record":{"source":{"id":"2411.02902","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-05T08:35:08Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CR","cs.LG"],"title_canon_sha256":"e9891058d43567369a20961c230da8f7f2bdeb9ae026dc3402c618db74d34bb6","abstract_canon_sha256":"7db5959a3eafa181dfe45a3e06126a8cee677390b6720048aaf10c2962b96a1c"},"schema_version":"1.0"},"canonical_sha256":"ebc4c7d110c9b3beb61d8aa33794d7ece0a16816c94c044d42fa9fb14f5da44e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:31:19.919752Z","signature_b64":"sUJrbFU6Vc1pZLuTEEsBhFg2gauG/7AJE5TkU3KetgoDvkuB2rY6D6YxPnkTNisSqwghhfFnEl/6R2HIbXQkBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ebc4c7d110c9b3beb61d8aa33794d7ece0a16816c94c044d42fa9fb14f5da44e","last_reissued_at":"2026-07-05T09:31:19.919345Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:31:19.919345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.02902","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":"2026-07-05T09:31:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+e9f7qthDpiqQtTpMp6/VW+vIxl9v87JYmPoJj8Yf4Rr42Rji7PASxFMuoiDNOjJhGC+v7hlO2bIhCfusCDMDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:11:30.670478Z"},"content_sha256":"4ca5616b459db86ba35d5463f5dcb1b0ed92b821d4e66720cfae2b47f14d254c","schema_version":"1.0","event_id":"sha256:4ca5616b459db86ba35d5463f5dcb1b0ed92b821d4e66720cfae2b47f14d254c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:5PCMPUIQZGZ35NQ5RKRTPFGX5T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Membership Inference Attacks against Large Vision-Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.CR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Elias Abad Rocamora, Francesco Tonin, Volkan Cevher, Yihang Chen, Yongtao Wu, Zhan Li","submitted_at":"2024-11-05T08:35:08Z","abstract_excerpt":"Large vision-language models (VLLMs) exhibit promising capabilities for processing multi-modal tasks across various application scenarios. However, their emergence also raises significant data security concerns, given the potential inclusion of sensitive information, such as private photos and medical records, in their training datasets. Detecting inappropriately used data in VLLMs remains a critical and unresolved issue, mainly due to the lack of standardized datasets and suitable methodologies. In this study, we introduce the first membership inference attack (MIA) benchmark tailored for var"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02902","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/2411.02902/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":"2026-07-05T09:31:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rcpgQ08iWpncN/XqyGWPhi/CIKnJcKcKaDZmNvTkZl3uDWEU/NOZaSDRF08ch0UeJj0EIAa9BpTsmTN3mP4uCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:11:30.671480Z"},"content_sha256":"f29008c4083fb5ff5c4789456e306406b6b9ca4d61ea16921cb4300327072f0e","schema_version":"1.0","event_id":"sha256:f29008c4083fb5ff5c4789456e306406b6b9ca4d61ea16921cb4300327072f0e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5PCMPUIQZGZ35NQ5RKRTPFGX5T/bundle.json","state_url":"https://pith.science/pith/5PCMPUIQZGZ35NQ5RKRTPFGX5T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5PCMPUIQZGZ35NQ5RKRTPFGX5T/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":"2026-08-14T08:11:30Z","links":{"resolver":"https://pith.science/pith/5PCMPUIQZGZ35NQ5RKRTPFGX5T","bundle":"https://pith.science/pith/5PCMPUIQZGZ35NQ5RKRTPFGX5T/bundle.json","state":"https://pith.science/pith/5PCMPUIQZGZ35NQ5RKRTPFGX5T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5PCMPUIQZGZ35NQ5RKRTPFGX5T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5PCMPUIQZGZ35NQ5RKRTPFGX5T","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":"7db5959a3eafa181dfe45a3e06126a8cee677390b6720048aaf10c2962b96a1c","cross_cats_sorted":["cs.AI","cs.CL","cs.CR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-05T08:35:08Z","title_canon_sha256":"e9891058d43567369a20961c230da8f7f2bdeb9ae026dc3402c618db74d34bb6"},"schema_version":"1.0","source":{"id":"2411.02902","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02902","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02902v1","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02902","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"pith_short_12","alias_value":"5PCMPUIQZGZ3","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"pith_short_16","alias_value":"5PCMPUIQZGZ35NQ5","created_at":"2026-07-05T09:31:19Z"},{"alias_kind":"pith_short_8","alias_value":"5PCMPUIQ","created_at":"2026-07-05T09:31:19Z"}],"graph_snapshots":[{"event_id":"sha256:f29008c4083fb5ff5c4789456e306406b6b9ca4d61ea16921cb4300327072f0e","target":"graph","created_at":"2026-07-05T09:31:19Z","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/2411.02902/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large vision-language models (VLLMs) exhibit promising capabilities for processing multi-modal tasks across various application scenarios. However, their emergence also raises significant data security concerns, given the potential inclusion of sensitive information, such as private photos and medical records, in their training datasets. Detecting inappropriately used data in VLLMs remains a critical and unresolved issue, mainly due to the lack of standardized datasets and suitable methodologies. In this study, we introduce the first membership inference attack (MIA) benchmark tailored for var","authors_text":"Elias Abad Rocamora, Francesco Tonin, Volkan Cevher, Yihang Chen, Yongtao Wu, Zhan Li","cross_cats":["cs.AI","cs.CL","cs.CR","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-05T08:35:08Z","title":"Membership Inference Attacks against Large Vision-Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02902","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":"sha256:4ca5616b459db86ba35d5463f5dcb1b0ed92b821d4e66720cfae2b47f14d254c","target":"record","created_at":"2026-07-05T09:31:19Z","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":"7db5959a3eafa181dfe45a3e06126a8cee677390b6720048aaf10c2962b96a1c","cross_cats_sorted":["cs.AI","cs.CL","cs.CR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-05T08:35:08Z","title_canon_sha256":"e9891058d43567369a20961c230da8f7f2bdeb9ae026dc3402c618db74d34bb6"},"schema_version":"1.0","source":{"id":"2411.02902","kind":"arxiv","version":1}},"canonical_sha256":"ebc4c7d110c9b3beb61d8aa33794d7ece0a16816c94c044d42fa9fb14f5da44e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ebc4c7d110c9b3beb61d8aa33794d7ece0a16816c94c044d42fa9fb14f5da44e","first_computed_at":"2026-07-05T09:31:19.919345Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:31:19.919345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sUJrbFU6Vc1pZLuTEEsBhFg2gauG/7AJE5TkU3KetgoDvkuB2rY6D6YxPnkTNisSqwghhfFnEl/6R2HIbXQkBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:31:19.919752Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.02902","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4ca5616b459db86ba35d5463f5dcb1b0ed92b821d4e66720cfae2b47f14d254c","sha256:f29008c4083fb5ff5c4789456e306406b6b9ca4d61ea16921cb4300327072f0e"],"state_sha256":"59170113546dc9a359175e55cba5c897041dbd65016efb034880ecfd39713878"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Aak5H8UXduiuTlyUYb0nRwSOqFuI2ZT10UTfPP+Xu6oqcH8tlFESV66QRK9XJ+P4BIoKpu/qjjWAH4cU14FpAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T08:11:30.694796Z","bundle_sha256":"7169d3d0c2ad1265d8c651b141d504fc2b1d11daf52bedfc17c271377ddc5516"}}