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Paper Citation Record · LEDGER

How Robust is Google's Bard to Adversarial Image Attacks?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 45 inbound Pith citation observations for arXiv:2309.11751.

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

pith.paper-citation-record.v1
2309.11751 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 45 of 45 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:25:58.416124Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • metadata mismatch0

External citation measurements

4
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 119b7a0e-e4eb-4763-b537-409dfd6025b5 · inbound

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions cites this paper.

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions How Robust is Google's Bard to Adversarial Image Attacks?

Reference 183

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arxiv_id, observed 2026-05-23T21:55:50.451983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T21:54:26.670284Z digest=sha256:1dac9659d6381b24979ae0e0bcbcb38eea0b22a8e72733144292f45eacef9090

Observation 4df322f1-892d-4aaa-a42a-8f4ca8e7e191 · inbound

Adversarial Hubness in Multi-Modal Retrieval cites this paper.

Adversarial Hubness in Multi-Modal Retrieval How Robust is Google's Bard to Adversarial Image Attacks?

Reference 19

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arxiv_id, observed 2026-05-23T06:42:39.743609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T06:39:36.039613Z digest=sha256:81210991ad7e018275f32bb0c575598eea211482c2cd77714b5385f5de7639ef

Observation 0cede9a2-b671-4098-82ae-3f68818a795a · inbound

On the robustness of multimodal language model towards distractions cites this paper.

On the robustness of multimodal language model towards distractions How Robust is Google's Bard to Adversarial Image Attacks?

Reference 6

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no resolver link, observed 2026-08-07T20:25:58.416124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:25:58.416124Z digest=sha256:5fa913a480c4eb9055b6a715612d9bbaa633078154e4c067d2ff80185fd7ae17

Observation ae7aa9af-d632-4c79-9ca2-d0ba784e5427 · inbound

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations cites this paper.

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations How Robust is Google's Bard to Adversarial Image Attacks?

Reference 100

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no resolver link, observed 2026-08-07T19:45:19.441527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:45:19.441527Z digest=sha256:f4be6d1cc2edac94d003eee4d8abc9ea590b25e5a343e403d512805a019cb7c9

Observation 2d4e5e9f-205b-4047-8889-f21988732d0b · inbound

Backdoor Cleaning without External Guidance in MLLM Fine-tuning cites this paper.

Backdoor Cleaning without External Guidance in MLLM Fine-tuning How Robust is Google's Bard to Adversarial Image Attacks?

Reference 18

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no resolver link, observed 2026-08-07T14:56:49.457828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:49.457828Z digest=sha256:b42482477f79ebe781746e8a6c48bb5110286f150813b87c99da446ceb581d79

Observation fab8b3b2-4a32-4dcf-b09c-6f8515aa05db · inbound

Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment cites this paper.

Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment How Robust is Google's Bard to Adversarial Image Attacks?

Reference 13

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no resolver link, observed 2026-08-07T13:35:50.982242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:35:50.982242Z digest=sha256:d59acc249ae46898d9775cdecbd99e97b9e593f4c47b0a7266dd4aff832dfa75

Observation 0c7dfc16-043a-4a3b-bac7-d25029946a27 · inbound

Disrupting Vision-Language Model-Driven Navigation Services via Adversarial Object Fusion cites this paper.

Disrupting Vision-Language Model-Driven Navigation Services via Adversarial Object Fusion How Robust is Google's Bard to Adversarial Image Attacks?

Reference 48

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unresolved
no resolver link, observed 2026-08-07T12:55:43.788243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:55:43.788243Z digest=sha256:302d949ae8bf82a782ea5b721b1d052bd7862c2600c7c8748d9f9722bdf0f760

Observation 19b04edd-5048-486a-a247-d1d459f40f8a · inbound

Spa-VLM: Stealthy Poisoning Attacks on RAG-based VLM cites this paper.

Spa-VLM: Stealthy Poisoning Attacks on RAG-based VLM How Robust is Google's Bard to Adversarial Image Attacks?

Reference 36

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no resolver link, observed 2026-08-07T13:21:41.966464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:41.966464Z digest=sha256:a29015c3e90987177bfee571f37ef74513c6f170c52dd0ff54b77fc77b122464

Observation d5086852-280e-487f-be1b-9cfb95f22b1e · inbound

Con Instruction: Universal Jailbreaking of Multimodal Large Language Models via Non-Textual Modalities cites this paper.

Con Instruction: Universal Jailbreaking of Multimodal Large Language Models via Non-Textual Modalities How Robust is Google's Bard to Adversarial Image Attacks?

Reference 8

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no resolver link, observed 2026-08-07T12:07:58.704370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:07:58.704370Z digest=sha256:7aa3986aeef86e53717867979fb63a789b844ab764cfb94ed50abe5d685d6706

Observation 2dad2463-c6ab-43f4-9408-1b83043da001 · inbound

Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs cites this paper.

Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs How Robust is Google's Bard to Adversarial Image Attacks?

Reference 13

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no resolver link, observed 2026-08-07T11:56:14.883612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:56:14.883612Z digest=sha256:f726806189e37e50994ae29a80cc7e213bc3d3005084ed07841be000d12adc6f

Observation 37777eec-ccad-48b1-bd52-14a4fd214294 · inbound

One Object, Multiple Lies: A Benchmark for Cross-task Adversarial Attack on Unified Vision-Language Models cites this paper.

One Object, Multiple Lies: A Benchmark for Cross-task Adversarial Attack on Unified Vision-Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 6

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no resolver link, observed 2026-08-06T18:40:52.995040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:40:52.995040Z digest=sha256:fd304ac1e0d553cb59c46b07cca3d3d315b90e70ff870a5d9377aeaefc116cad

Observation b9826d94-4775-43a8-a039-7694b7706696 · inbound

Adversarial-Guided Diffusion for Multimodal LLM Attacks cites this paper.

Adversarial-Guided Diffusion for Multimodal LLM Attacks How Robust is Google's Bard to Adversarial Image Attacks?

Reference 11

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no resolver link, observed 2026-08-06T11:02:14.960784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:02:14.960784Z digest=sha256:054e55f39c9941444004346d9f8cd7de895c803cd56ab7c39faee28b673561bb

Observation cea59753-6b5b-476f-9168-1609347dbbe5 · inbound

Blockchain Network Analysis using Quantum Inspired Graph Neural Networks & Ensemble Models cites this paper.

Blockchain Network Analysis using Quantum Inspired Graph Neural Networks & Ensemble Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 3

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no resolver link, observed 2026-08-05T21:22:36.758764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:22:36.758764Z digest=sha256:0f603733fe3e1c6df692d81b5a04239984c04a0e50811956013073b373b45e52

Observation 57f1cbdc-0e67-4dba-89fb-280b33986645 · inbound

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey cites this paper.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey How Robust is Google's Bard to Adversarial Image Attacks?

Reference 222

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no resolver link, observed 2026-08-05T20:29:05.380161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:29:05.380161Z digest=sha256:18926062ebdc22c42808f1165398b544d7755a746edadb0a6765b735abaff055

Observation 48fac66d-f646-488d-8871-08488efd4c13 · inbound

On Surjectivity of Neural Networks: Can you elicit any behavior from your model? cites this paper.

On Surjectivity of Neural Networks: Can you elicit any behavior from your model? How Robust is Google's Bard to Adversarial Image Attacks?

Reference 17

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no resolver link, observed 2026-08-05T16:00:48.380311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:00:48.380311Z digest=sha256:84e60a2669bab2cb4d1d033f2e280a77f236757a0073ede7bc6a67497686e94c

Observation b9798a55-6502-4a83-9d66-1fb0777b9aad · inbound

VISOR++: Universal Visual Inputs based Steering for Large Vision Language Models cites this paper.

VISOR++: Universal Visual Inputs based Steering for Large Vision Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 3

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unresolved
no resolver link, observed 2026-08-04T13:45:26.355350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:45:26.355350Z digest=sha256:4af25e7c0d2b75e0a5e5b13a05e8bd6c6994ca0228e42f44e7dd67110b3d235b

Observation b1d7631d-f54d-427d-a6df-e24c31f22c16 · inbound

Contrastive Spectral Rectification: Test-Time Defense towards Zero-shot Adversarial Robustness of CLIP cites this paper.

Contrastive Spectral Rectification: Test-Time Defense towards Zero-shot Adversarial Robustness of CLIP How Robust is Google's Bard to Adversarial Image Attacks?

Reference 2023

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no resolver link, observed 2026-08-03T07:47:37.500987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T07:47:37.500987Z digest=sha256:39239d6d270ae4a04c65df7443ab78a0ae88939d699835e474ffbffb0fcbf698

Observation 2bae9e10-95eb-4f38-933a-b7f15bcf9762 · inbound

Universal Adversarial Attacks against Closed-Source MLLMs via Target-View Routed Meta Optimization cites this paper.

Universal Adversarial Attacks against Closed-Source MLLMs via Target-View Routed Meta Optimization How Robust is Google's Bard to Adversarial Image Attacks?

Reference 3

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verified exact
arxiv_id, observed 2026-05-16T09:27:40.976188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T09:26:14.799360Z digest=sha256:edf0fb56b5f1e6c0349b2774e6efec7c40d2441aa0af98350a9e276cb65ad984

Observation c044521e-4429-4c7a-8a05-06b9c5f725fa · inbound

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection cites this paper.

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection How Robust is Google's Bard to Adversarial Image Attacks?

Reference 7

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verified exact
arxiv_id, observed 2026-05-16T06:40:42.324184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T06:39:17.785715Z digest=sha256:0b493037b690b1fbc817272438ae98119a2195d342928b0591875fe72560b1f6

Observation 9c0e6acb-57cf-44da-9229-264e8654e016 · inbound

Grounding-Driven Attack: Improving Encoder-based Adversarial Transferability against Large Vision-Language Models cites this paper.

Grounding-Driven Attack: Improving Encoder-based Adversarial Transferability against Large Vision-Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 13

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unresolved
no resolver link, observed 2026-08-03T02:57:45.790570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:57:45.790570Z digest=sha256:d7eb265a9bbb60905354f4efc25b3547794bb5cb5e84f3ec924cfe1ab747ccab

Observation 53d0f926-60b8-4177-85f5-47de7a482584 · inbound

Beyond Standard Benchmarks: A Systematic Audit of Vision-Language Model's Robustness to Natural Semantic Variation Across Diverse Tasks cites this paper.

Beyond Standard Benchmarks: A Systematic Audit of Vision-Language Model's Robustness to Natural Semantic Variation Across Diverse Tasks How Robust is Google's Bard to Adversarial Image Attacks?

Reference 9

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verified exact
arxiv_id, observed 2026-05-10T21:55:52.672143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T20:26:42.128350Z digest=sha256:909b7a076addb322a6797aab12fb83c88f8f45f89f1448034526a0469cebcf5d

Observation c6d7064b-edcc-473f-9ad8-d105eea83a6d · inbound

Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization cites this paper.

Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization How Robust is Google's Bard to Adversarial Image Attacks?

Reference 42

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verified exact
arxiv_id, observed 2026-05-15T20:36:35.220145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T20:35:17.075890Z digest=sha256:3ac528bf59aef966b82ba64b2723e8f24391a70a1bde4895d0aac1f5cc490e09

Observation 20d236fa-b5b4-41bc-ac5a-c1bd68724170 · inbound

One Perturbation, Two Failure Modes: Probing VLM Safety via Embedding-Guided Typographic Perturbations cites this paper.

One Perturbation, Two Failure Modes: Probing VLM Safety via Embedding-Guided Typographic Perturbations How Robust is Google's Bard to Adversarial Image Attacks?

Reference 5

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verified exact
arxiv_id, observed 2026-05-11T23:21:15.095557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T17:24:05.847988Z digest=sha256:cdb4f1a67e564c5c0e778ecb9c924caa81e287b3b0a79116f4e71d3d695ad971

Observation 08c6da3e-2e00-4d3d-beaa-5f1a43258ead · inbound

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems cites this paper.

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems How Robust is Google's Bard to Adversarial Image Attacks?

Reference 9

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verified exact
arxiv_id, observed 2026-05-11T10:06:02.848262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:39:32.595169Z digest=sha256:ffed809283e18fb936ba33387549399b0d74c24bf1ebd542d16b0f7fd3e15503

Observation d8a8d895-2175-424c-8cff-33f32f044ff6 · inbound

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems cites this paper.

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems How Robust is Google's Bard to Adversarial Image Attacks?

Reference 9

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verified exact
arxiv_id, observed 2026-05-11T04:20:58.067575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T01:46:54.430546Z digest=sha256:39b71e8a5807cca36228de2efc9f670c018bfb28bd44245eeb66061d6aec4037

Observation c4064cd7-94a0-4bba-b10a-0f8ad332a365 · inbound

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems cites this paper.

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems How Robust is Google's Bard to Adversarial Image Attacks?

Reference 9

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verified exact
arxiv_id, observed 2026-05-15T07:15:12.004444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T07:11:16.568353Z digest=sha256:21a856d2c13b156ad5ceb48c50fd30dd32d248251c7a3cf540d32dcc828459f6

Observation d98c9a77-0b92-4fa6-a6c0-e5c465ad64dc · inbound

Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment cites this paper.

Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment How Robust is Google's Bard to Adversarial Image Attacks?

Reference 40

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verified exact
arxiv_id, observed 2026-05-11T04:10:59.823103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-11T01:53:46.652759Z digest=sha256:53ee97a0af18e27e6944845166b9904f3f06e8a1440c53ff626c94b8b7c6715e

Observation e91af393-e689-47fa-93a8-d85c2ca21834 · inbound

Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing cites this paper.

Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing How Robust is Google's Bard to Adversarial Image Attacks?

Reference 46

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metadata mismatch
arxiv_id, observed 2026-05-12T05:51:27.633916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T04:50:08.866969Z digest=sha256:032d19272def9d7ed78b0403607c64bdf1b755cade23e746e4be01775df3d0c7

Observation 61444bc2-f1bd-4862-a947-847bd1befac7 · inbound

SafeSteer: A Decoding-level Defense Mechanism for Multimodal Large Language Models cites this paper.

SafeSteer: A Decoding-level Defense Mechanism for Multimodal Large Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 15

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metadata mismatch
arxiv_id, observed 2026-05-13T06:57:27.613113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-13T06:56:10.053418Z digest=sha256:18f42bbec162801e36a38f7c0ce9e1d92b1df0cf9341d197556fc35d4d703a97

Observation 230dfffd-57e1-488a-bd7f-dc9d2ae6785a · inbound

Attention Hijacking: Response Manipulation Across Queries in Vision-Language Models cites this paper.

Attention Hijacking: Response Manipulation Across Queries in Vision-Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 11

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metadata mismatch
arxiv_id, observed 2026-05-20T14:28:21.617868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T14:25:10.603780Z digest=sha256:7e18a8616a7580e27d7edc3caed0e2521f93776db858096b2af95c5757db5baf

Observation e38fb1bd-8314-4a26-b4d7-bb29cb0ae5e9 · inbound

DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models cites this paper.

DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 12

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verified exact
arxiv_id, observed 2026-05-20T18:33:37.971752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T18:31:48.770507Z digest=sha256:062170d59860c46096527f799a79278e6bc41a85030053afd06c723d5c1507fc

Observation 6236a050-80fa-44b6-9f30-d0e05e6c610c · inbound

DMN: A Compositional Framework for Jailbreaking Multimodal LLMs with Multi-Image Inputs cites this paper.

DMN: A Compositional Framework for Jailbreaking Multimodal LLMs with Multi-Image Inputs How Robust is Google's Bard to Adversarial Image Attacks?

Reference 33

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metadata mismatch
arxiv_id, observed 2026-05-20T10:23:12.313384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T10:19:11.536555Z digest=sha256:734659c522bb0891b73f5d3bb432176ad06b7d2373ea6f0c24989e4579b21497

Observation c3736c71-022c-4ebe-ab92-701ef8721148 · inbound

REFLECTOR: Internalizing Step-wise Reflection against Indirect Jailbreak cites this paper.

REFLECTOR: Internalizing Step-wise Reflection against Indirect Jailbreak How Robust is Google's Bard to Adversarial Image Attacks?

Reference 50

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metadata mismatch
arxiv_id, observed 2026-05-21T06:19:41.967990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-21T06:16:01.040236Z digest=sha256:31d67d2c50bf55ded884feb49e3e63397fdb0b1b15436ef5042f4a4e1bdd7bf1

Observation 9b6aff5d-4824-462f-9766-6000b583a986 · inbound

Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs cites this paper.

Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs How Robust is Google's Bard to Adversarial Image Attacks?

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-22T01:25:52.665642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T01:25:06.528845Z digest=sha256:a7654228880e41bcc67b8d6954a68d52b97aa2bed8b6a9bc107590a60c2e54a1

Observation 7176d271-9528-4a1d-af55-a273d94059b4 · inbound

Unveiling the Fragility of Vision-Language Models: Multi-Modal Adversarial Synergy via Texture-Constrained Perturbations and Cross-Modal Optimization cites this paper.

Unveiling the Fragility of Vision-Language Models: Multi-Modal Adversarial Synergy via Texture-Constrained Perturbations and Cross-Modal Optimization How Robust is Google's Bard to Adversarial Image Attacks?

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-06-29T18:23:50.907500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T18:17:52.158294Z digest=sha256:ccf1192ae0b703e5bc680e9a906622d9a05a899985fdfe89a1fb81a77cd5c943

Observation 60ce9223-c0d2-443b-a3a1-bd6eaea06829 · inbound

MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language Models cites this paper.

MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 102

Resolution
verified exact
arxiv_id, observed 2026-06-27T21:51:18.133090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T21:47:22.295896Z digest=sha256:994675cd2054ecea1d91429e93e11f16d17890293ddeffd01d98d6710b8add3c

Observation ae37be47-fcbc-4caa-8d76-c8d91acfe061 · inbound

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges cites this paper.

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges How Robust is Google's Bard to Adversarial Image Attacks?

Reference 84

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T01:27:31.013372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T16:33:28.848573Z digest=sha256:9f324eb27390e89456723558ea375f1d6108f6b4f445be48497507166e5d51c5

Observation f4acd54c-a215-4805-a3ab-068c58c96969 · inbound

REALM: A Unified Red-Teaming Benchmark for Physical-World VLMs cites this paper.

REALM: A Unified Red-Teaming Benchmark for Physical-World VLMs How Robust is Google's Bard to Adversarial Image Attacks?

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:29:45.751085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T08:44:45.853401Z digest=sha256:43b59e62445bdd1fb4282939fdcafcbbbbfa98ce7545b9c8f505c1e414bf2420

Observation 394c9a55-2e2d-4187-8c94-40c0ebe07590 · inbound

Steal the Patch Size: Adversarially Manipulate Vision-Language Models cites this paper.

Steal the Patch Size: Adversarially Manipulate Vision-Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T19:37:18.461154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-07-02T19:30:19.691473Z digest=sha256:778e69695951e33c95acd886394c75bf391226a1e9f90cf8bb249185d5bbe860

Observation 81fcb0aa-cfa2-4775-a5ff-1298bcc2e682 · inbound

On Adversarial Vulnerability of Vision-Language Models through the Lens of Intermediate Spectral Subspaces cites this paper.

On Adversarial Vulnerability of Vision-Language Models through the Lens of Intermediate Spectral Subspaces How Robust is Google's Bard to Adversarial Image Attacks?

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-07-09T12:56:14.861381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-09T12:55:34.631248Z digest=sha256:76db390ef90cc974e8f38d92036baf3bb9824fe2a42ebaea51c602d7dfba407d

Observation d8af849a-9f06-4645-b272-1e94bbc19e24 · inbound

3D FaceShell: Attribute Transfer in 3D Face Avatars as a VLM Defense Mechanism cites this paper.

3D FaceShell: Attribute Transfer in 3D Face Avatars as a VLM Defense Mechanism How Robust is Google's Bard to Adversarial Image Attacks?

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-02T07:51:46.960018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:51:46.960018Z digest=sha256:fbeaddfef89a8d9927cfac0e68abc6d907f3f314217230fbd191ae1438659223

Observation 72348382-e4f1-4b55-a73a-4db267e12b10 · inbound

Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model cites this paper.

Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model How Robust is Google's Bard to Adversarial Image Attacks?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T13:51:21.218412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:51:21.218412Z digest=sha256:0161455e0a2d547e010fb1bf9183687bb7c50d5cd7cc4d569a6f2e1c789cd95d

Observation a8ef4c8d-5344-4a18-abd2-5aa8bbb13338 · inbound

GeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation cites this paper.

GeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation How Robust is Google's Bard to Adversarial Image Attacks?

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-01T08:42:16.741551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T08:42:16.741551Z digest=sha256:e31933762a8e5eb4eb6fe8bde6ba6611f0fd2042f4eb3c0a433e034074a7c907

Observation e850dde1-1e7e-48b8-b5fe-3c29d8735989 · inbound

Visual Token Compression Enhances Robustness of MLLMs cites this paper.

Visual Token Compression Enhances Robustness of MLLMs How Robust is Google's Bard to Adversarial Image Attacks?

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-01T13:10:37.295272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:10:37.295272Z digest=sha256:49717502d5df6ccf22df2f858e280e04cc609fa828cfc3641a713c0f6c1e420f

Observation 44fa4744-60a7-4df2-ab71-72f17dd4d8cc · inbound

Two Sides of the Same Coin: Co-Evolving Search for Cross-Task Attacks on Vision-Language Models cites this paper.

Two Sides of the Same Coin: Co-Evolving Search for Cross-Task Attacks on Vision-Language Models How Robust is Google's Bard to Adversarial Image Attacks?

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-04T13:51:18.175083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T13:51:18.175083Z digest=sha256:5044c4fc8ad70fc2f94ff618a26f7975d41175e6d50a71710c1292371cf6d708