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Paper Citation Record · LEDGER

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models

As of 18 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.16760.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.16760 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:42:43.269669Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d204f17c-1770-4b55-97e0-ac8438e63efb · outbound

This paper cites an unresolved cited work.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Unresolved cited work

Reference 1

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Observation 41261ed3-e84b-4928-af26-2b0df8d2067b · outbound

This paper cites GPT-4 Technical Report.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models GPT-4 Technical Report

Reference 2

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source=pdf_text observed=2026-08-06T23:42:38.611607Z digest=sha256:ab7135075ca87cc61856553f583aaa557081c83ae3f34ff4004d8518d4914f0f

Observation fbfa95c3-7b3a-4a3b-a2db-1260d716177a · outbound

This paper cites https://together.ai (2025), accessed: 2025- 06.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models https://together.ai (2025), accessed: 2025- 06

Reference 3

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:38.735036Z digest=sha256:a6dd3b708a78f50b794069675622c9d8ac7d0914fcb8a9023837086784b62b99

Observation 22ca9b99-9f0f-4a3f-a0e6-42b811b09326 · outbound

This paper cites Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

Reference 4

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source=pdf_text observed=2026-08-06T23:42:38.875494Z digest=sha256:7bae57ce3cbd9da769434ac14b3bd482446313f2ef77615b1b500ce6efe97b63

Observation 864b1d06-e646-4b04-8962-2d50ea9004ea · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 5

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source=pdf_text observed=2026-08-06T23:42:38.985969Z digest=sha256:c8f4de0321b7bc39dd20fb66e8478be410a7bc43fbe772d5d42b408ce456b9b4

Observation 9af55388-72f1-4d6d-8645-b79be8e28636 · outbound

This paper cites an unresolved cited work.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Unresolved cited work

Reference 6

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6bc3847a-7a3e-4c32-af17-778fd7fab464 · outbound

This paper cites Jailbreaking Black Box Large Language Models in Twenty Queries.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 7

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source=pdf_text observed=2026-08-06T23:42:39.216412Z digest=sha256:037e01f10ef68fc068a7b56e1dd638f96ae30e6116411f51855b9131a5a1dbeb

Observation 58d4f8c3-ac1a-4392-9c3d-2dfed39261b3 · outbound

This paper cites In: Proceedings of the AAAI Confer- ence on Artificial Intelligence.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: Proceedings of the AAAI Confer- ence on Artificial Intelligence

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:39.317685Z digest=sha256:55e62a5f1b0a8bb47ce846e5af736fc97a0a0379af3d73a90578ba9c3e64d513

Observation 7d6339da-4eb8-4313-87ea-e6e94e8870cf · outbound

This paper cites arXiv preprint arXiv:2402.10601 (2024).

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models arXiv preprint arXiv:2402.10601 (2024)

Reference 9

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source=pdf_text observed=2026-08-06T23:42:39.438993Z digest=sha256:6abda0f51be9937cd59b4588f5fd1ffb00bca1ca65c7709494a79dc4b3549835

Observation c63fd57d-3bff-4954-9b0f-a10b07749024 · outbound

This paper cites GPT-4o System Card.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models GPT-4o System Card

Reference 10

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source=pdf_text observed=2026-08-06T23:42:39.589878Z digest=sha256:3d453288c3aa6be50e30cd8ece09b1ac466099abfa2bf9bf968d3c95497ecb0a

Observation 835a3e93-2361-4b44-b00c-33241bd8a543 · outbound

This paper cites https://pypi.org/project/easyocr/1.7.1/ (2023), accessed: 2024-02-09.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models https://pypi.org/project/easyocr/1.7.1/ (2023), accessed: 2024-02-09

Reference 11

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:39.787246Z digest=sha256:f7a557887f0132d07e1c52228c2b0e6e3b730666608aec343c054f57b19c46c2

Observation ff304ecb-6229-456a-9f57-fe650cf25fc4 · outbound

This paper cites Baseline Defenses for Adversarial Attacks Against Aligned Language Models.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Baseline Defenses for Adversarial Attacks Against Aligned Language Models

Reference 12

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source=pdf_text observed=2026-08-06T23:42:39.896114Z digest=sha256:44e4a4c42c381b33faa9b392fff3b7081b30ef33ffd403d0b1de850a732960b1

Observation 190e3b4f-485e-4189-80c1-27120b0fcbb8 · outbound

This paper cites In: International conference on machine learning.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: International conference on machine learning

Reference 13

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raw_fallback, observed 2026-08-06T23:42:48.839995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:40.096590Z digest=sha256:e9a05b2558f5cf840f482b9025346dc2d9dd3d007d55cd9f909849ed75d95a94

Observation b6ab3f03-9479-4fe9-a079-99a02e47787f · outbound

This paper cites In: European Conference on Computer Vision.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: European Conference on Computer Vision

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:40.255076Z digest=sha256:10132f15e405f9c90eb6ff6cea7d906a61445ff22c6b8c2137aede7807cdc7b7

Observation 6cbea444-5a75-419d-a0aa-fce307d28d7a · outbound

This paper cites AmpleGCG: Learning a Universal and Transferable Generative Model of Adversarial Suffixes for Jailbreaking Both Open and Closed LLMs.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models AmpleGCG: Learning a Universal and Transferable Generative Model of Adversarial Suffixes for Jailbreaking Both Open and Closed LLMs

Reference 15

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source=pdf_text observed=2026-08-06T23:42:40.394893Z digest=sha256:92e711b21798b715209ad20bc53c10fad6b704617270474e9434928a08c5e061

Observation 982b7b19-af86-4167-9b65-c5b88ab5fb9e · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 16

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raw_fallback, observed 2026-08-06T23:42:48.304761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:40.504823Z digest=sha256:885444d8c34e107f0018e46249ffb41eb34c330e692e848546c6d3887f45ce85

Observation e904f8bd-0f34-42c2-893e-6422cd680200 · outbound

This paper cites In: 33rd USENIX Security Symposium (USENIX Security 24).

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: 33rd USENIX Security Symposium (USENIX Security 24)

Reference 17

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:40.643737Z digest=sha256:9b81d6433a98f30b72fdc27c400c70936bd92359d655242c4a80d31152d71ddb

Observation f947fcdf-6ac4-4019-b54a-c4a7f1f57347 · outbound

This paper cites AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

Reference 18

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source=pdf_text observed=2026-08-06T23:42:40.739634Z digest=sha256:8ed6edaa0cecc63d2754239dfe8caacb8ed13f5c19c6c42ad0386e9a1d97f46d

Observation 79ed48ae-7ca7-4c59-b021-fe15e5a9a1cb · outbound

This paper cites JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks

Reference 19

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source=pdf_text observed=2026-08-06T23:42:40.840053Z digest=sha256:034f3cec9a9b13acb725cc1cc3a68e3c3b4dbe25dfa495d0ba6dc9e82d12dcd2

Observation 68c36517-5c9c-4150-af93-e2a760df8424 · outbound

This paper cites Proceedings of Machine Learning Research235, 35181–35224 (2024).

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Proceedings of Machine Learning Research235, 35181–35224 (2024)

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:40.967020Z digest=sha256:3fdc0e76ee1c00521f92b3c4cb6bc4ccf78c8c17d2a6a05b9d5350a2073c385e

Observation b4af6ff0-a14e-441c-983f-55d47c155843 · outbound

This paper cites Jailbreaking Attack against Multimodal Large Language Model.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Jailbreaking Attack against Multimodal Large Language Model

Reference 21

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source=pdf_text observed=2026-08-06T23:42:41.206394Z digest=sha256:1ea77033d194a01e7d501c656c515057238f2e37072f6f440c18ab84a87e3b44

Observation 2896ce1f-c4c1-4d4e-aa3f-cb99aedcc184 · outbound

This paper cites https://platform.openai.com/ docs/guides/moderation (2024), accessed: 2024-02-09.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models https://platform.openai.com/ docs/guides/moderation (2024), accessed: 2024-02-09

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:41.294752Z digest=sha256:57212d8b6cfdf9b06342b64f3818c3072d3ceac010c0334789239e6cb3b83421

Observation db215771-bb22-4178-8afe-facd88371c62 · outbound

This paper cites https://openai.com/index/ gpt-4-1/ (2025), accessed: 2025-06.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models https://openai.com/index/ gpt-4-1/ (2025), accessed: 2025-06

Reference 23

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:41.417982Z digest=sha256:cda6d0176d5f1ddf3677a4504e3762d21dffff5ebc68a077e9f28598124e1121

Observation 6cd89896-2a5f-442b-896b-2f847f6f69fe · outbound

This paper cites In: The Twelfth International Conference on Learning Representations (2023).

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: The Twelfth International Conference on Learning Representations (2023)

Reference 25

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:41.766685Z digest=sha256:a4f350d3fe265de61bdce32486ec3795870ff12810186df33ab1bd0883fafd43

Observation 5ea30eb6-5d5f-4bf6-9d01-dc0b3a1c8436 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 26

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source=pdf_text observed=2026-08-06T23:42:41.934834Z digest=sha256:dca08c83f956996ee5ffe1bd350be17ba5440e96a931db1f03c47eb12fa2a29f

Observation 8a3a3a96-ad71-4c9d-b489-e026c2e90ac6 · outbound

This paper cites an unresolved cited work.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Unresolved cited work

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:42.057341Z digest=sha256:875340bc311a93440c29f0b0a6eac880100a3e1823f691f383206dffff7db5cd

Observation 81fb3274-f7c0-480e-b65b-cb8f14eb9ac0 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 28

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:42.179391Z digest=sha256:682bc82494b20fe52ff67415e8c754f0207492239ebfb51b8c46f0d58eba9d63

Observation e188cac1-90db-4257-90e6-106dfa414d3e · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 29

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source=pdf_text observed=2026-08-06T23:42:42.384833Z digest=sha256:6864fd23b1ece41b0af83a5ea968d40f44084df1c961d5bacc3121feb7e7d701

Observation c05cc6b6-df0a-4b80-a1be-aba46ecb7652 · outbound

This paper cites In: Proceedings of the 32nd ACM International Conference on Multime- dia.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: Proceedings of the 32nd ACM International Conference on Multime- dia

Reference 30

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raw_fallback, observed 2026-08-06T23:42:46.649677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:42.488866Z digest=sha256:f5e67482d1853a4b0d507b6bd61b999d81cc7aca8e7d85ace9d7e6e5b5d497b7

Observation f1443ad0-5f48-4817-8693-1e369d10af80 · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models CogVLM: Visual Expert for Pretrained Language Models

Reference 31

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source=pdf_text observed=2026-08-06T23:42:42.594752Z digest=sha256:3eab80edef9ec4bbacdd576c3cd4239e22a2da3340a880ab79f7e349de5d0862

Observation 99ec7fa8-3e09-4ae9-8ff6-46491f808e1f · outbound

This paper cites Qwen2 Technical Report.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Qwen2 Technical Report

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:42.674859Z digest=sha256:951b2cc0f11d52e7f33e5557b0bc3c84e79f44de891b9d16960e287054aa3c9b

Observation ab1fac99-7b25-45e7-aefb-79ca5e1c65eb · outbound

This paper cites A Survey on Multimodal Large Language Models.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models A Survey on Multimodal Large Language Models

Reference 33

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:42.738914Z digest=sha256:1370a94c94c6ca628ed539dd270e062ffc0514d6618cfe7a96ba3a9ac98ac9e3

Observation feee3bb0-1f51-4cd0-a73d-c45e8e78c78d · outbound

This paper cites Low-Resource Languages Jailbreak GPT-4.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Low-Resource Languages Jailbreak GPT-4

Reference 34

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no resolver link, observed 2026-08-06T23:42:42.798103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:42.798103Z digest=sha256:e8214ef0221bef48a734d927770150989455f1fecfcbb819aebd96b90bb2a06c

Observation 820d8f86-6714-42f3-8fd9-c2763326728f · outbound

This paper cites GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher

Reference 35

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no resolver link, observed 2026-08-06T23:42:42.971360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:42.971360Z digest=sha256:872505d626fc5f60fe3d3525dbc1b88a2ff9ad95a25d4b91ece8e42816979a93

Observation ad1bbe46-1f26-4f24-96cd-381d9f5f9ab1 · outbound

This paper cites In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguis- tics (V olume 1: Long Papers).

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguis- tics (V olume 1: Long Papers)

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-06T23:42:46.457553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8282f364-aaa8-42d3-86a1-11243466b13c · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:43.107250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:43.107250Z digest=sha256:7ddcc5429c3ad290cea7e7d95a3cdab382bf71c057704038542805fa112a9384

Observation f732304b-780e-4793-b2b8-d551cfef81b4 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:43.172464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:43.172464Z digest=sha256:6af86170e99971434fa5c69cadc2e96ec9d62bcb49edfb5a895a480fbf1530f2

Observation 19f92926-8a56-4b08-abb8-150322b8b4cb · outbound

This paper cites an unresolved cited work.

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:42:46.123015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:42:43.269669Z digest=sha256:d0b186f25e10d27207b0b1eb96a3939ef1343b284d76e0e5abe77093f7a3dae4

Pith citing papers

No inbound Pith citation observations are available.