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Paper Citation Record · LEDGER

Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 39 inbound Pith citation observations for arXiv:2310.10844.

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

pith.paper-citation-record.v1
2310.10844 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 39 of 39 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:58:57.366800Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:08:22.541839Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 74c1ca33-73c4-4ed6-8e5d-7e99d1e14373 · inbound

A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 65

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arxiv_id, observed 2026-05-15T07:21:39.890253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T07:21:39.440092Z digest=sha256:bc13be888e42d9b32afbfd2a4c42ee1077e81fba095452c3dbaaffd31d5b67a5

Observation e8e573e6-674f-46f1-a7e7-a12d2283bf32 · inbound

Jailbreak Attacks and Defenses Against Large Language Models: A Survey cites this paper.

Jailbreak Attacks and Defenses Against Large Language Models: A Survey Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 78

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arxiv_id, observed 2026-05-15T02:20:44.818202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T02:20:44.368219Z digest=sha256:4a5a4fe09d0dbf2f0643db38809abdc46a12d50434da5c3d315d13989e6937c6

Observation 1524854c-f491-4395-8ffc-62d3e82d8094 · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 132

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arxiv_id, observed 2026-05-23T20:58:26.130679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T20:58:16.237327Z digest=sha256:b763cb7f80d829e0c1e77e13ed4d0681fa28a5d070bb8a7b4675d1a1768ffb2a

Observation 98563063-0bb6-47e8-9adf-04d707e99bc7 · inbound

Multi-Agent Collaboration Mechanisms: A Survey of LLMs cites this paper.

Multi-Agent Collaboration Mechanisms: A Survey of LLMs Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 115

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arxiv_id, observed 2026-05-13T15:54:54.251086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T15:54:54.146003Z digest=sha256:11557d6360b4deb53760a51b4d9901f0cfac7b50818de9dacb3998d89a2f0b24

Observation e34b13c3-19a3-4d5e-8853-4d3a75b4b9b5 · inbound

`Do as I say not as I do': A Semi-Automated Approach for Jailbreak Prompt Attack against Multimodal LLMs cites this paper.

`Do as I say not as I do': A Semi-Automated Approach for Jailbreak Prompt Attack against Multimodal LLMs Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 4

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no resolver link, observed 2026-08-09T17:58:57.366800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T17:58:57.366800Z digest=sha256:442bc3d25862c604faa2869ce138270484199294400afb82f0bff83d4da7964b

Observation 02ad21f5-47e0-411d-a5f6-8f19eb505419 · inbound

Large Language Model Adversarial Landscape Through the Lens of Attack Objectives cites this paper.

Large Language Model Adversarial Landscape Through the Lens of Attack Objectives Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 17

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no resolver link, observed 2026-08-09T10:29:49.967993Z

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source=pdf_text observed=2026-08-09T10:29:49.967993Z digest=sha256:963849b078156486153e06348c96b4900f6f14495b69b870dc223d95be49af1f

Observation af0cb92b-f7bd-42ad-9c34-e3a1ece7f36f · inbound

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities cites this paper.

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 65

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no resolver link, observed 2026-08-09T14:47:15.309285Z

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source=arxiv_source observed=2026-08-09T14:47:15.309285Z digest=sha256:44b0be47e9e8f97121d380946a8009baaac0fa5f35625403d703aa226e5dc69a

Observation c71a1b11-70f6-4b5c-b8eb-1d8ad2eb2d85 · inbound

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 162

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no resolver link, observed 2026-08-08T19:15:25.548189Z

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source=pdf_text observed=2026-08-08T19:15:25.548189Z digest=sha256:81e2a79afe0b207b44873edcc52b2acea6339b209d7e154ecdec39e268be1a04

Observation 8cde1543-df87-4c5d-817a-1cfe0574c2f7 · inbound

Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks cites this paper.

Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 16

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no resolver link, observed 2026-08-08T04:37:28.522854Z

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source=pdf_text observed=2026-08-08T04:37:28.522854Z digest=sha256:06c49a1eab867f14876f23188bb3f6a7840b054c6de06291ec41b393d9f38339

Observation 8cbd3b69-1c96-4b50-b6ce-9eee7078f365 · inbound

Towards an AI co-scientist cites this paper.

Towards an AI co-scientist Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 23

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arxiv_id, observed 2026-05-11T13:02:44.397504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T13:02:43.571234Z digest=sha256:22965438eeb49e494fff29c08d3bfa436c9857e87e1af42f2e1d533fe14cae12

Observation dac3146d-6eb7-4f86-ad36-f6a65494106d · inbound

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion cites this paper.

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 21

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arxiv_id, observed 2026-05-23T00:15:14.841571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T00:13:08.603115Z digest=sha256:df67b3f374b69268ae10ee559f980b9aa695e4ff1dc8ad54088761ef83fd369c

Observation 1eea4041-1481-4f28-acc6-3fe938db8e38 · inbound

Set-LLM: A Permutation-Invariant LLM cites this paper.

Set-LLM: A Permutation-Invariant LLM Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 31

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no resolver link, observed 2026-08-07T15:25:54.737108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:25:54.737108Z digest=sha256:d31003a8526ffbceb564c9ee65a3333ae351c06f975f5a1ad82b66a3dd5b5eff

Observation 3a5fd50e-8463-4378-b555-0104ecddeb33 · inbound

Security Concerns for Large Language Models: A Survey cites this paper.

Security Concerns for Large Language Models: A Survey Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 54

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no resolver link, observed 2026-08-07T14:27:03.630698Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:27:03.630698Z digest=sha256:69fd57dac771ede21149e5e7e7e511161f076da720fa589e34c16652230ad02b

Observation b79b05df-58c3-41ab-ad1c-60b79ca3b741 · inbound

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study cites this paper.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 39

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no resolver link, observed 2026-08-07T13:32:58.625420Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:58.625420Z digest=sha256:8f5947658f887115eedb51fb5f970e4cc8f8b3396458ccf57becaa25a520a999

Observation 6834f2c5-27b5-456d-8141-d43d9c8f53e1 · inbound

Securing AI Systems: A Guide to Known Attacks and Impacts cites this paper.

Securing AI Systems: A Guide to Known Attacks and Impacts Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 77

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no resolver link, observed 2026-08-06T21:50:28.218630Z

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source=pdf_text observed=2026-08-06T21:50:28.218630Z digest=sha256:1a01d1d3f6d1afa48c2fc06cbd158037b0c5c85ba9db03deb97f34ea918b68a3

Observation ee72f87d-2f44-4743-9d6a-aef92a1fc866 · inbound

Explicit Vulnerability Generation with LLMs: An Investigation Beyond Adversarial Attacks cites this paper.

Explicit Vulnerability Generation with LLMs: An Investigation Beyond Adversarial Attacks Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 19

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no resolver link, observed 2026-08-06T17:46:00.241746Z

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source=pdf_text observed=2026-08-06T17:46:00.241746Z digest=sha256:717f847d228a0dd8055a390e4f3d06c89b91b15f03c0bbe36932cc467d70d0bf

Observation 6992bebe-bcdb-43ba-b341-0577b25b048c · inbound

Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix Approach cites this paper.

Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix Approach Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 31

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no resolver link, observed 2026-08-06T17:40:06.330557Z

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source=arxiv_source observed=2026-08-06T17:40:06.330557Z digest=sha256:cdd6b59566a1a9a3ea4f6dd8dbd144d4ef37812148194d1f32e2b267da6d323b

Observation 6351fe2a-e6e3-4c08-a69a-59f01f6f8c61 · inbound

Understanding the Supply Chain and Risks of Large Language Model Applications cites this paper.

Understanding the Supply Chain and Risks of Large Language Model Applications Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 17

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no resolver link, observed 2026-08-06T14:45:42.889327Z

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source=pdf_text observed=2026-08-06T14:45:42.889327Z digest=sha256:783dd35217e2e5e4398170f0373bd93443f2399028540b9eef90b854deb69081

Observation c1ac3ea4-1a10-4592-a21c-de29beabe937 · inbound

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation cites this paper.

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 139

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no resolver link, observed 2026-08-05T20:31:45.522393Z

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source=pdf_text observed=2026-08-05T20:31:45.522393Z digest=sha256:9d0255cc92a45d39178fbf26bd967969c3bda48630ec640d9712a8bd409c72ec

Observation 44ca7e1b-5139-496e-bbf4-e753db7dc7d5 · inbound

SALMAN: Stability Analysis of Language Models Through the Maps Between Graph-based Manifolds cites this paper.

SALMAN: Stability Analysis of Language Models Through the Maps Between Graph-based Manifolds Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 27

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no resolver link, observed 2026-08-05T17:14:35.079560Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:14:35.079560Z digest=sha256:7b16e9c465ca8843bbf84a76d2139dd3c25716411067d3864898f37a7a3496a3

Observation b68e77f6-7fa0-49d6-b4a4-7614bad807bc · inbound

An Empirical Study of Vulnerable Package Dependencies in LLM Repositories cites this paper.

An Empirical Study of Vulnerable Package Dependencies in LLM Repositories Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 59

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no resolver link, observed 2026-08-05T14:22:35.177263Z

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source=pdf_text observed=2026-08-05T14:22:35.177263Z digest=sha256:aa504a6fecd0ebefcaff86d4fe95b122c7e9517a3fdae1677b7ec728cdbe4a00

Observation 6c917c07-f06e-4e09-9d7a-21b822e1d425 · inbound

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security cites this paper.

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 15

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no resolver link, observed 2026-08-04T23:09:41.453737Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:09:41.453737Z digest=sha256:33f648dfc5df3470ec73d0649df8575215e739563852613ef15cb4959ebf2124

Observation 6ed93282-b66a-4bc7-a8ab-a7e9ab9c3fbe · inbound

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses cites this paper.

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 160

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no resolver link, observed 2026-08-04T09:25:53.143092Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:25:53.143092Z digest=sha256:92f75fc690a40752b09d8ffbec3acc5ce2b593513a9cbc4718378375e6ad2cbe

Observation b5b273ae-1c0c-4d21-88f8-d8da143f6a12 · inbound

A First Look at the Security Issues in the Model Context Protocol Ecosystem cites this paper.

A First Look at the Security Issues in the Model Context Protocol Ecosystem Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 40

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arxiv_id, observed 2026-05-18T06:12:26.302997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T06:10:58.928119Z digest=sha256:7df227ede015ab877a4c9225a982a01d1ed315286505b03c990f6f139bbeaac0

Observation 4e723586-e1e6-48c2-8e3f-11c739240747 · inbound

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts cites this paper.

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 12

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arxiv_id, observed 2026-05-18T04:25:52.247115Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T04:22:54.943043Z digest=sha256:39b277626bed5485046659a761fd714f2d7e4b3b90d18e78885c77e44ab23c89

Observation aa4d4a4f-1265-466b-9d7a-681337864367 · inbound

CluCERT: Certifying LLM Robustness via Clustering-Guided Denoising Smoothing cites this paper.

CluCERT: Certifying LLM Robustness via Clustering-Guided Denoising Smoothing Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 2020

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no resolver link, observed 2026-08-03T19:08:41.705708Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:08:41.705708Z digest=sha256:ed32cb16821e4bfedb6501211057bcbb145de3dca2ee88341859db14e61eb9c8

Observation 04cb83cd-e566-4c35-a53d-72324df03873 · inbound

Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models cites this paper.

Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 6

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metadata mismatch
arxiv_id, observed 2026-05-16T20:23:23.516334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T20:22:29.726790Z digest=sha256:16e09a027a11a9fb1b9f0b2ca04fcb62acf62e9d6bc8d3dc92db6e77fa92d750

Observation 5a3290d8-0c80-4b51-8cee-a1d855d0efc9 · inbound

Gaslight, Gatekeep, V1-V3: Early Visual Cortex Alignment Shields Vision-Language Models from Sycophantic Manipulation cites this paper.

Gaslight, Gatekeep, V1-V3: Early Visual Cortex Alignment Shields Vision-Language Models from Sycophantic Manipulation Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 16

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verified exact
arxiv_id, observed 2026-05-10T13:10:26.186623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T13:09:35.407790Z digest=sha256:95134f1e5dcc2205b29f31c91ac85ead7ceef3e8952a17d5e1617ad24cbc94a0

Observation f3e92f99-34c8-40b6-a4e5-307100ad83db · inbound

An Interpretable and Scalable Framework for Evaluating Large Language Models cites this paper.

An Interpretable and Scalable Framework for Evaluating Large Language Models Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 50

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arxiv_id, observed 2026-05-11T04:41:01.637098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:08:25.577363Z digest=sha256:18b760563debf123e4f4de3e71043731f02fe0d888c9d18896558b95eadaedf5

Observation abb620a2-85c3-4de1-9e3a-c966a5873279 · inbound

LLM-Agnostic Semantic Representation Attack cites this paper.

LLM-Agnostic Semantic Representation Attack Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 25

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arxiv_id, observed 2026-05-12T08:21:24.228171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T01:14:08.629862Z digest=sha256:2eb5ad893ef5490f0288da4f51fcc92dcc6d97e89fb5d5ff204483f4dd2a06e4

Observation 79fd79eb-7288-49d5-aac4-04b80a41d753 · inbound

Same Model, Different Weakness: How Language and Modality Reshape the Jailbreak Attack Surface in Frontier MLLMs cites this paper.

Same Model, Different Weakness: How Language and Modality Reshape the Jailbreak Attack Surface in Frontier MLLMs Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 10

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arxiv_id, observed 2026-05-25T05:05:22.798995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-25T05:03:57.453043Z digest=sha256:1c42914b80d49ce07c339b2a63f616fd3d366f8b0255808e93b0ace62d6ed230

Observation 3a375261-2b3f-4875-bda3-ed23dbd53e5f · inbound

Evolving Skill-Structured Attack Memory Enhances LLM Jailbreaking cites this paper.

Evolving Skill-Structured Attack Memory Enhances LLM Jailbreaking Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 5

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arxiv_id, observed 2026-06-29T07:13:16.287228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T07:10:50.007951Z digest=sha256:f9a2719a0247b26009f928d7b0036332a14f4e89882f459a0b854e4a15580773

Observation 56ef63d0-e4b3-456d-9648-61be75c445c7 · inbound

SkillGuard: A Permission-Centric Framework for Agent Skill Security cites this paper.

SkillGuard: A Permission-Centric Framework for Agent Skill Security Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T03:26:28.541049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T10:07:36.872590Z digest=sha256:6c560863fdfafc6fab208dd276d88805641c112c67e5c350185a626287c54057

Observation b0e5784f-0ab3-4c41-a731-8912067b9e97 · inbound

SkillGuard: A Permission-Centric Framework for Agent Skill Security cites this paper.

SkillGuard: A Permission-Centric Framework for Agent Skill Security Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 29

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no resolver link, observed 2026-07-14T18:32:00.165926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T18:32:00.165926Z digest=sha256:99afa35a8b9806493986662446c315a14b426789777788e1e56d1f038d5ada45

Observation ad514d80-3526-43bd-a294-ee1abca59f0c · inbound

When Large Language Models Fail in Healthcare: Evaluating Sensitivity to Prompt Variations cites this paper.

When Large Language Models Fail in Healthcare: Evaluating Sensitivity to Prompt Variations Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:07:17.625693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T21:41:20.354463Z digest=sha256:8d033fdf676bf9f67f89c71586601694fb6cb30453d75be6cf3b51b3867f32d0

Observation 49c231b4-8fe8-4cac-9398-c8cfd46eecd7 · inbound

S-GBT: Smooth Growth Bound Tensor for Certified Robustness Against Word Substitution Attacks in NLP cites this paper.

S-GBT: Smooth Growth Bound Tensor for Certified Robustness Against Word Substitution Attacks in NLP Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T14:08:22.543118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T07:09:20.940256Z digest=sha256:89adbbf2d1dea8d266522f6c2f3a73bea2dc91d8f9cdf867052aba8746514643

Observation 512c7575-777a-4ffb-8de9-aedc6c442639 · inbound

Just Testing, Move Along: Evasion of LLM-based System Log Interpretation by Prompt Injection cites this paper.

Just Testing, Move Along: Evasion of LLM-based System Log Interpretation by Prompt Injection Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-31T22:00:18.860503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T22:00:18.860503Z digest=sha256:c7312c5cc570f57716dadfa0384840b826c7a3af933eaed540130e9c0f1b7cac

Observation b6e1d9ef-c30c-42d9-bc0d-2da1eacecc9e · inbound

Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges cites this paper.

Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 195

Resolution
unresolved
no resolver link, observed 2026-08-03T00:55:31.990231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T00:55:31.990231Z digest=sha256:578c7b26b642d695defb7ba21eacf7dd4f3f6680995eb5acc8c161440b5576ad

Observation 7ed41cf7-1526-48e1-8dd2-6471e029d600 · inbound

SoK: Intent-Oriented Systematization of Multi-Turn LLM Jailbreaks cites this paper.

SoK: Intent-Oriented Systematization of Multi-Turn LLM Jailbreaks Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T00:32:02.310068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:32:02.310068Z digest=sha256:71003bbdeecc69654e9119fc529c33a600f6c667b83a4daf0dbca4fb2f176469