Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T09:02:41.029778Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2510.17759.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T09:02:41.029778Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
37 of 37 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 091f8ee0-ab77-4c76-aad0-fd5b72694fcc · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Qwen2.5-VL Technical Report
Reference 1
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Observation c6ff87cc-55f6-4fd3-83f7-8132cfddcc6e · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Trust-vlm: Thorough red-teaming for uncovering safety threats in vision-language models
Reference 2
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Observation 822e213c-bd6e-4428-a4fe-d57ff9776962 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models JPS: Jailbreak Multimodal Large Language Models with Collaborative Visual Perturbation and Textual Steering
Reference 3
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Observation 13326619-084b-42db-916e-3bb3d21b4adf · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Gonzalez, Ion Stoica, and Eric P
Reference 4
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Observation 8eaa35df-b236-42ce-a2d1-b764b1728477 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Eta: Evaluating then aligning safety of vision language models at inference time
Reference 5
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Observation 6962335d-e8ab-44d5-97ea-00b444f5db40 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Scaling rectified flow transformers for high-resolution image synthesis
Reference 6
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Observation 7d688941-46ad-4aaf-9f2d-088d0a311427 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Figstep: Jailbreaking large vision-language models via typographic visual prompts
Reference 7
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Observation 9adf6efa-39f9-4f04-a303-024b5adda4f7 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models The VLLM Safety Paradox: Dual Ease in Jailbreak Attack and Defense
Reference 8
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Observation 414a6897-861b-4f39-b9c4-a1ef332f6833 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Lora: Low-rank adaptation of large language models
Reference 9
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Observation a4b938b8-0588-4903-b0f2-26c079ca1d0a · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Images are achilles' heel of alignment: Exploiting visual vulnerabilities for jailbreaking multimodal large language models
Reference 10
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Observation c709635b-4625-4f7d-b9fa-534eb2b0a28c · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Images are achilles’ heel of alignment: Exploiting visual vulnerabilities for jailbreaking multimodal large language models
Reference 11
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Observation bf9bab15-904c-455e-bd2e-9bdf7b4e6b1f · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Vl-trojan: Multimodal instruction backdoor attacks against autoregressive visual language models
Reference 12
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Observation 72f10972-37fe-4be9-af0f-d6733e68f3ec · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Visual instruction tuning
Reference 13
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Observation 257b9b0b-1e0d-493c-b832-35d95ca85419 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Arondight: Red teaming large vision language models with auto-generated multi-modal jailbreak prompts
Reference 14
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Observation 81994794-73d5-4737-902b-fadf39160117 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models VERA: Variational Inference Framework for Jailbreaking Large Language Models
Reference 15
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Observation c588d445-d65f-4da7-bfee-0f88f4afb94e · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Backdooring vision-language models with out-of-distribution data
Reference 16
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Observation 59cd7582-ec3a-4e5a-9246-11362bc47eb0 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Character
Reference 17
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Observation 47eb88d5-8b7d-4544-b473-3a07b91582a7 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Forsyth, and Dan Hendrycks
Reference 18
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Observation 497efb19-bc19-44ac-8cc9-4ceb95cea2f9 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Jailbreaking Attack against Multimodal Large Language Model
Reference 19
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Observation 4649dad8-2c8f-4f16-9969-4600e5505cf2 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Hello gpt-4o, 2024 a
Reference 20
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Observation da2bd73e-ae9c-44d6-a656-f1326093b6b4 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Gpt-4o mini: Advancing cost-efficient intelligence, 2024 b
Reference 21
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Observation dadd5531-ff1d-44e6-aedc-3ccc2cf2827b · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Learning To See But Forgetting To Follow: Visual Instruction Tuning Makes LLMs More Prone To Jailbreak Attacks
Reference 22
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Observation 44df4ca0-2727-458e-80f4-516314822216 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Visual adversarial examples jailbreak aligned large language models
Reference 23
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Observation ae799f24-33b2-466b-b074-5fb104fdb242 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Vision-LLMs Can Fool Themselves with Self-Generated Typographic Attacks
Reference 24
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Observation 2549ffbb-e9e0-43bd-af0f-37b5366acbe2 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Jailbreak in pieces: Compositional adversarial attacks on multi-modal language models
Reference 25
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Observation 8ec290b4-3d51-490c-9ec3-ad4fe12b499a · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models A strongreject for empty jailbreaks
Reference 26
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Observation 5aa58fde-4c0b-4fa3-9308-6ec03bda1952 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Imgtrojan: Jailbreaking vision-language models with ONE image
Reference 27
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Observation 7c02fb54-f84d-4526-8ab4-26af9073ccc9 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Ideator: Jailbreaking and benchmarking large vision-language models using themselves
Reference 28
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Observation 7e210163-3f8a-407e-8757-f27ce44d7a38 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Jailbreak large vision-language models through multi-modal linkage
Reference 29
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Observation 52927ac3-116f-4a00-bce0-c5ab5b265af2 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Simple statistical gradient-following algorithms for connectionist reinforcement learning
Reference 30
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Observation 91f7918b-66f7-4817-ab8c-7c893431ab87 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Distraction is all you need for multimodal large language model jailbreaking
Reference 31
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Observation daee661d-3b7b-47f8-a12d-ecb072bc89bb · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Anyattack: Towards large-scale self-supervised adversarial attacks on vision-language models
Reference 32
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Observation 74d883df-13ad-462b-9443-1746eb1de9d7 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Reference 33
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Observation 573a73fc-0bb4-4d46-a44b-f90e820b36ac · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models write newline
Reference 34
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Observation c2d0ce8c-4fe0-4f23-8812-cf1c2369cf0a · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models @esa (Ref
Reference 35
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Observation 399611c8-40de-44ec-86f1-68bd2449fc8c · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Unresolved cited work
Reference 36
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Observation 488101bd-a5ae-4d55-91c9-568c30c5f659 · outbound
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models Unresolved cited work
Reference 37
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No inbound Pith citation observations are available.