{"as_of":"2026-08-22T11:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cb8372a0fb195e7f58e77c4d89e500395fba383d55b55dfc483a62fe65db44da","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":13,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T23:18:31.320117Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-09T00:25:48.524527Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-12T16:52:27.650257Z","title":"Sa-attack: Improving adversar- ial transferability of vision-language pre-training models via self-augmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13136","last_updated":"2024-11-20T08:58:59Z","snapshot_observed_at":"2026-08-20T22:04:21.491930Z","submitted_at":"2024-11-20T08:58:59Z","title":"TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T16:52:27.650257Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2411.13136"},"observation_digest":"sha256:0446b371c4736cdb7dd06bac8a73f5bccc844bd825a16d02f91c507e3e21758a","observation_id":"8dedbda0-6fba-4535-acf3-d9cf26e09085","resolution":{"observed_at":"2026-08-12T16:52:27.650257Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":"2312.04913","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-07-09T00:25:48.524527Z","title":"Sa-attack: Improving adversarial transferability of vision-language pre-training models via self-augmentation","venue":"cs.CV","work_id":"1da15fe3-a676-4665-9071-1a0be694f3ef","year":2023},"citing_paper":{"arxiv_id":"2502.05206","last_updated":"2026-04-14T16:10:41Z","snapshot_observed_at":"2026-08-20T09:36:18.005089Z","submitted_at":"2025-02-02T05:14:22Z","title":"Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety","version":6},"reference_index":223,"source":"pdf_text","source_observed_at":"2026-05-23T04:39:04.591722Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2502.05206"},"observation_digest":"sha256:f2ba2b04049fd4c316ee0457345eb662095e200a1b22562779cc961f7d27e335","observation_id":"8d85a39e-df1e-4f18-bd37-d5cf99405b2d","resolution":{"observed_at":"2026-05-23T04:42:33.995280Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-08T10:56:49.171617Z","title":"Sa-attack: improving adversarial transferability of vision-language pre-training models via self-augmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08079","last_updated":"2025-03-03T01:35:58Z","snapshot_observed_at":"2026-08-22T00:19:07.975724Z","submitted_at":"2025-02-12T02:53:27Z","title":"MAA: Meticulous Adversarial Attack against Vision-Language Pre-trained Models","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-08T10:56:49.171617Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2502.08079"},"observation_digest":"sha256:6297774c5dfab090c55c6ebc4d743b526f73e0242edafe7d8e2bd34bf997c5be","observation_id":"24c044c8-0174-49a2-9003-9321ec9c3ba3","resolution":{"observed_at":"2026-08-08T10:56:49.171617Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-15T23:18:31.320117Z","title":"Sa-attack: Improving adversarial transferability of vision-language pre-training models via self-augmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.05528","last_updated":"2025-05-29T23:50:01Z","snapshot_observed_at":"2026-08-19T19:16:41.662800Z","submitted_at":"2025-05-08T11:59:13Z","title":"X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP","version":3},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-15T23:18:31.320117Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2505.05528"},"observation_digest":"sha256:a0aba51890a4d665c2122eb725487429c67489b946b587f074ae219266e21a94","observation_id":"fccbfcfc-52ea-4b42-88ff-eb110ba54d7c","resolution":{"observed_at":"2026-08-15T23:18:31.320117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-07T13:35:52.215725Z","title":"Sa- attack: Improving adversarial transferability of vision-language pre-training models via self- augmentation.arXiv preprint arXiv:2312.04913, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21494","last_updated":"2025-05-27T17:56:57Z","snapshot_observed_at":"2026-08-21T09:16:11.921930Z","submitted_at":"2025-05-27T17:56:57Z","title":"Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:35:52.215725Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2505.21494"},"observation_digest":"sha256:88beb7e0bb8922dfec59be6f1185ff97bb40502b40e64b6d1614a5f66f20e688","observation_id":"ecdbbe7a-cca9-4aa1-9760-674bf2d4c7be","resolution":{"observed_at":"2026-08-07T13:35:52.215725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-07T12:35:35.832321Z","title":"SA- Attack: Improving adversarial transferability of vision- language pre-training models via self-augmentation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.24227","last_updated":"2025-05-30T05:30:02Z","snapshot_observed_at":"2026-08-16T08:44:16.129177Z","submitted_at":"2025-05-30T05:30:02Z","title":"Light as Deception: GPT-driven Natural Relighting Against Vision-Language Pre-training Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T12:35:35.832321Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2505.24227"},"observation_digest":"sha256:2ea4b19851866a43776ab80b8319f4bc0aceb06723032444034dc6d7a268087c","observation_id":"94ac1984-3a7a-4856-a826-f280259693f9","resolution":{"observed_at":"2026-08-07T12:35:35.832321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-07T11:09:06.917630Z","title":"Sa-attack: Improving adversar- ial transferability of vision-language pre-training models via self-augmentation.arXiv preprint arXiv:2312.04913, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.05394","last_updated":"2025-09-12T16:12:48Z","snapshot_observed_at":"2026-08-09T05:43:52.010041Z","submitted_at":"2025-06-03T19:42:48Z","title":"Attacking Attention of Foundation Models Disrupts Downstream Tasks","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:09:06.917630Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2506.05394"},"observation_digest":"sha256:634f436c8dd062135d28ee79608283873003083289f93d1fcca3d774214d4371","observation_id":"23f999c7-dc3c-40cf-a482-00828550a3bc","resolution":{"observed_at":"2026-08-07T11:09:06.917630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-03T07:47:37.524533Z","title":"Sa-attack: Improving adversarial transferability of vision- language pre-training models via self-augmentation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.19210","last_updated":"2026-06-09T16:01:52Z","snapshot_observed_at":"2026-08-16T09:52:01.671907Z","submitted_at":"2026-01-27T05:24:45Z","title":"Contrastive Spectral Rectification: Test-Time Defense towards Zero-shot Adversarial Robustness of CLIP","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T07:47:37.524533Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2601.19210"},"observation_digest":"sha256:e4188bbc869e58f5967d6d4291ec9ff9320b3f8ac94c80003b351fbdeafd307d","observation_id":"da6ce663-1381-4da2-a57b-edb21fe0b030","resolution":{"observed_at":"2026-08-03T07:47:37.524533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":"2312.04913","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-07-09T00:25:48.524527Z","title":"Sa-attack: Improving adversarial transferability of vision-language pre-training models via self-augmentation","venue":"cs.CV","work_id":"1da15fe3-a676-4665-9071-1a0be694f3ef","year":2023},"citing_paper":{"arxiv_id":"2604.04630","last_updated":"2026-04-06T12:29:49Z","snapshot_observed_at":"2026-08-16T23:45:01.753809Z","submitted_at":"2026-04-06T12:29:49Z","title":"Multimodal Backdoor Attack on VLMs for Autonomous Driving via Graffiti and Cross-Lingual Triggers","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T20:30:29.032353Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2604.04630"},"observation_digest":"sha256:1e8f003a6ab565aaf040ffda6ca9d5d7129e688b25fe5fa74d87ed5f7e77aa17","observation_id":"dd58d9e1-6764-4356-8264-85ca43fd7782","resolution":{"observed_at":"2026-05-10T21:55:49.697599Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":"2312.04913","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-07-09T00:25:48.524527Z","title":"Sa-attack: Improving adversarial transferability of vision-language pre-training models via self-augmentation","venue":"cs.CV","work_id":"1da15fe3-a676-4665-9071-1a0be694f3ef","year":2023},"citing_paper":{"arxiv_id":"2605.17577","last_updated":"2026-05-17T18:07:08Z","snapshot_observed_at":"2026-08-15T22:01:31.311467Z","submitted_at":"2026-05-17T18:07:08Z","title":"TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-20T14:20:49.278545Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2605.17577"},"observation_digest":"sha256:9fabb53bb18276acd95a74a2e0edea21d6c56957a6eed8b6fad207af544a84d8","observation_id":"bcd4b880-946a-4d83-b2e8-42ad63b05a3f","resolution":{"observed_at":"2026-05-20T14:23:21.524504Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":"2312.04913","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-07-09T00:25:48.524527Z","title":"Sa-attack: Improving adversarial transferability of vision-language pre-training models via self-augmentation","venue":"cs.CV","work_id":"1da15fe3-a676-4665-9071-1a0be694f3ef","year":2023},"citing_paper":{"arxiv_id":"2607.05783","last_updated":"2026-07-07T03:15:00Z","snapshot_observed_at":"2026-08-20T01:17:02.721022Z","submitted_at":"2026-07-07T03:15:00Z","title":"Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-07-09T00:16:03.334057Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2607.05783"},"observation_digest":"sha256:e95bc381a352f156e5fd92fabd8ea62a388ec9ced56f8206e80b18243e6e0765","observation_id":"571cc4c3-5b68-4a4a-8560-666cf13937f5","resolution":{"observed_at":"2026-07-09T00:25:48.525831Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-02T01:17:29.774162Z","title":"arXiv preprint arXiv:2312.04913 (2023) GeoDetect 17","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.14737","last_updated":"2026-07-16T09:02:38Z","snapshot_observed_at":"2026-08-19T08:13:40.463143Z","submitted_at":"2026-07-16T09:02:38Z","title":"GeoDetect: Geometric Adversarial Detection for VLPs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T01:17:29.774162Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2607.14737"},"observation_digest":"sha256:58f7b78d15fd0f7d6f37c0fcff6a5719b66aff0984a72a508f7c83561e24b1e1","observation_id":"332058d4-c0bf-4d66-8adc-40c33ede1efd","resolution":{"observed_at":"2026-08-02T01:17:29.774162Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04913","snapshot_observed_at":"2026-08-02T00:37:17.010873Z","title":"SA-Attack: Improving adversarial transferability of vision-language pre-training models via self- augmentation.arXiv preprint, arXiv:2312.04913, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.14974","last_updated":"2026-07-16T13:28:59Z","snapshot_observed_at":"2026-08-10T18:19:26.788845Z","submitted_at":"2026-07-16T13:28:59Z","title":"On Success and Simplicity: A Second Look at Transferable Vision-Language Attack Pipeline","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T00:37:17.010873Z"},"links":{"cited_paper":"/paper/2312.04913","citing_paper":"/paper/2607.14974"},"observation_digest":"sha256:b8231c2f683b4b3d5a1de8d5934d81886c990a4030b3abff9cefbab230854b4f","observation_id":"e0d5434f-f3b0-44b2-b3f7-5fb29cc261ca","resolution":{"observed_at":"2026-08-02T00:37:17.010873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2312.04913/citation-record","integrity":"/paper/2312.04913/integrity","json":"/paper/2312.04913/citation-record.json","paper":"/paper/2312.04913"},"outbound":[],"paper":{"arxiv_id":"2312.04913","last_updated":"2023-12-08T09:08:50Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-22T00:18:48.053727Z","submitted_at":"2023-12-08T09:08:50Z","title":"SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2312.04913."}