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Paper Citation Record · LEDGER

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context

As of 23 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 2 inbound Pith citation observations for arXiv:2412.16359.

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

pith.paper-citation-record.v1
2412.16359 v3

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:44:19.840925Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:31:01.310794Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:31:07.402925Z

Reference resolution

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7cf9934f-9dfc-4941-9b72-8807e32bbf42 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.592837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.645303Z digest=sha256:31e8fd9c3d0ff8124c74f5a6fe3b0556c4af28f1b39160378dd5e391c9b2ab74

Observation 95a87020-9183-4868-b118-1b447ca09004 · outbound

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

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

Reference 2

Resolution
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no resolver link, observed 2026-08-11T10:44:19.652542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.652542Z digest=sha256:66952962b9d510e332d283ac3f58593e5fc77405d92131c654c40e3025f8ed37

Observation 6c2f5552-848f-47fd-80af-a3f281cdc6c1 · outbound

This paper cites AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents

Reference 3

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no resolver link, observed 2026-08-11T10:44:19.659746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.659746Z digest=sha256:0b6da185ec7c7c6c2c01c7b385bca60adf08a57caab02dd96690c590bb361500

Observation c7d4ffcd-e97b-4784-a699-96542affcf40 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.566948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.666387Z digest=sha256:a314b04cd56755eaace86a045d4916f10924b77957132938f36aaf1ae551d8a0

Observation 0d7719e5-432f-41d8-a6bd-30be24480f82 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.548437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.673376Z digest=sha256:7f3f407cde85086877947e0b3728e0e0f27da08271b18a44171e5710a6a66d3e

Observation 8eae148a-cd7e-4be3-b44f-1bb950989062 · outbound

This paper cites HotFlip: White-Box Adversarial Examples for Text Classification.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context HotFlip: White-Box Adversarial Examples for Text Classification

Reference 6

Resolution
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no resolver link, observed 2026-08-11T10:44:19.680938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.680938Z digest=sha256:f270553ccea935a9b3e9aea6721811f88f8fd17376e1b8276f1fe2b12de8999d

Observation 122bc6a9-25da-420d-9ad6-0beeda1cd709 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 7

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no resolver link, observed 2026-08-11T10:44:19.688131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.688131Z digest=sha256:bd45c30762358be10e7b60db3bf6e8eae2824398d5638573befbca33c52761dd

Observation 90a9549c-4351-42b6-87c0-e022d7051b25 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.516566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.694196Z digest=sha256:69285a78361396746d344a9b2be0d0b22eb51da27a3343308711587179828a3c

Observation e82f2d31-88af-4147-9bbe-f9cec9148ce5 · outbound

This paper cites Gradient-based Adversarial Attacks against Text Transformers.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Gradient-based Adversarial Attacks against Text Transformers

Reference 9

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no resolver link, observed 2026-08-11T10:44:19.699801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.699801Z digest=sha256:0dddc7e186c648a1cc59c665f917b2d6893ff4889292547b444160b9a8d9e878

Observation 66c244f6-dfc7-4446-b813-ef461f302272 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.495340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.705729Z digest=sha256:a2f0d796d4f37d805fa9a1a6c11c07bcfdfab0f1168e9175a863f74376149fce

Observation acbde766-9d5a-4ab0-b71c-de5f3bb2b66b · outbound

This paper cites Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models

Reference 11

Resolution
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no resolver link, observed 2026-08-11T10:44:19.711412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.711412Z digest=sha256:6e8dd4ed563b1e0abcd93ea8f0bedd0b804ddd4c66849381332029266dca7220

Observation 44ebeef0-b777-4b36-ae85-b51f3780fdd7 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.717713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.717713Z digest=sha256:dcbd9ae20a4c540b4729add128c052cffd6d2ff0ae9bf44879c7d91639e3b4d7

Observation eb54cdca-2502-4cd6-9953-ea1ba9e7eada · outbound

This paper cites SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecurity.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecurity

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.722784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.722784Z digest=sha256:80f04cc432ab1ca0cbbf9531bc7281d5d86932479551dbfa11d473a600398a44

Observation 78e647bc-9706-4999-9d6f-1f345a261f8f · outbound

This paper cites Adversarial Machine Learning at Scale.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Adversarial Machine Learning at Scale

Reference 14

Resolution
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no resolver link, observed 2026-08-11T10:44:19.728555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.728555Z digest=sha256:ea7cf25d6b5c2f833d939db2584e58930be2896a9198742b4760c3384155e10e

Observation 79a66612-b6fc-4fae-8171-4df096c42a1d · outbound

This paper cites TextBugger: Generating Adversarial Text Against Real-world Applications.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context TextBugger: Generating Adversarial Text Against Real-world Applications

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.734253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.734253Z digest=sha256:8d0f8a7c034e4694c9c5dd3f1649d138c2efc006c4fffc44f2043b9d7e11f76d

Observation 3f198369-4710-4620-ab8b-4e69b1ae8cfc · outbound

This paper cites BERT-ATTACK: Adversarial Attack Against BERT Using BERT.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context BERT-ATTACK: Adversarial Attack Against BERT Using BERT

Reference 16

Resolution
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no resolver link, observed 2026-08-11T10:44:19.740214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.740214Z digest=sha256:3955c9f195f32ef2c66eadd3985e83083206e4c0c33981ada1f8e70b3cef0ecd

Observation 4a0315c6-e57f-4187-a6bb-64cc091d511c · outbound

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

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.746792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.746792Z digest=sha256:6e5a3711262edbbaa082d96163952dc0a9797378e53dae180051d54629308037

Observation 1088d775-a680-459d-b613-dcea56bdfff8 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 18

Resolution
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no resolver link, observed 2026-08-11T10:44:19.753680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.753680Z digest=sha256:8fcc7cda78175983554ddbb4d5118ab47d7289176e1dd044eeb43e704aa57356

Observation 21a60d1c-2d29-4f65-98de-6082cda87140 · outbound

This paper cites AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs

Reference 19

Resolution
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no resolver link, observed 2026-08-11T10:44:19.758947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.758947Z digest=sha256:18a971f1e46268d2b4b1b5f632d3920e8cbe5d2b27bbf7429afb9958d9a7a10e

Observation 82c82a01-9e48-4364-886e-3c912879cc6e · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.442274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.764869Z digest=sha256:83021c843b02374df53e6c40c44b8a1483223c1ee7ecc85ba3f08a2e59b4dd4c

Observation 792f3373-6ea7-48b1-b82a-480edb7427d1 · outbound

This paper cites Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.770969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.770969Z digest=sha256:b5ff19734f1ea977119fdd590f84e40dffeb23deb23fb2afa3f25108a7efc8c5

Observation 2ce057e0-4901-4d1d-aec0-b37ff5a5fb82 · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.418374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.778209Z digest=sha256:4cac264a8c609c9f9e9e136e3f6b4509762ff5c8c5886a1d5d2d097a06923d9f

Observation eba4e0e8-bf05-48fa-a959-cf248d508c2e · outbound

This paper cites Universal Adversarial Triggers for Attacking and Analyzing NLP.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Universal Adversarial Triggers for Attacking and Analyzing NLP

Reference 23

Resolution
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no resolver link, observed 2026-08-11T10:44:19.783529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.783529Z digest=sha256:6497908cd5d05ca8debfe03881eb659c4db68be6c89acf18d2a77d8ee9ed723e

Observation 38ada602-4900-41a9-9807-c72916032b1e · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.396123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.788865Z digest=sha256:7249caa4fd8b15c4c3310680b35a49d852317fef18a5c4194fa1f8821565a35e

Observation feb18855-6d7a-46c4-a474-be4a5f92c13b · outbound

This paper cites On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.794327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.794327Z digest=sha256:9f06f246607c923f514938e13cf2fc68168c2769f619e6117ace364cf5d0d622

Observation 0c936b39-9611-4ed6-84b1-1b1f5b4b0bc7 · outbound

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

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Large Language Model Adversarial Landscape Through the Lens of Attack Objectives

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.799687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.799687Z digest=sha256:6cdb016d3ea875a0c4d0a5e4e632c7c69b824cacc7e5f50525f8224389a2e1f6

Observation d7bf8982-e188-4dc2-a424-ac80756b5b01 · outbound

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

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Jailbreak Attacks and Defenses Against Large Language Models: A Survey

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.805763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.805763Z digest=sha256:8e950c0c2eb6c7b8a2f07217230cf9068f49312151b7d335b15c45d1063d29d8

Observation f438edb7-b26f-4217-95d9-697edd7e4b3a · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:44:20.374982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T10:44:19.810946Z digest=sha256:f5add2d82f961d73aae0fe0ad8850c5fb95cc571589658a78d8e2664bcbb8ce5

Observation bfcb6699-afe3-4573-aed0-581e9806c88c · outbound

This paper cites an unresolved cited work.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Unresolved cited work

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.816609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.816609Z digest=sha256:26520901a0c39a749c638ef2eaa0a5f174fb81a6e1e613b1364504970b2da4dc

Observation af2d1ba5-abfd-4c1d-aaf3-d3201245ef6f · outbound

This paper cites PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.829310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.829310Z digest=sha256:0a85b4ceab01bf1519620eb4ec2b11de3eae0547be573506bfa7794cfc4a4763

Observation 13fc85b4-f8db-420e-9a13-195617f3cc22 · outbound

This paper cites AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.835361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.835361Z digest=sha256:8e39399fbfb18aadb3f1f0cc7c6c353e01c0839a205da27bf65b39e613113af4

Observation eb4cd759-115e-457f-8302-3edf8ae7b1c0 · outbound

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

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.840925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.840925Z digest=sha256:d5d755a6a78ea11253c54f7732e0db30bf22c78665fb4f5df62da7d290ead52a

Observation 1bfadeb6-8459-4318-9093-3c5171416817 · outbound

This paper cites Advances in Neural Information Processing Systems 36 (2023), 46595–46623.

Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context Advances in Neural Information Processing Systems 36 (2023), 46595–46623

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T10:44:19.824065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:44:19.824065Z digest=sha256:542d903a82a5287dbff08bd41a971feeb8728d10483a24776e9628732db4ec8b

Pith citing papers

Observation dc0f6c11-7bf5-4c72-a118-20f132d7d14a · inbound

Adversarial Machine Learning Attacks on Financial Reporting via Maximum Violated Multi-Objective Attack cites this paper.

Adversarial Machine Learning Attacks on Financial Reporting via Maximum Violated Multi-Objective Attack Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:31:07.407612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:31:01.310794Z digest=sha256:9f43645acbb1b77bdd5e36854f79792f6e912e6c9a858d9bb84260634db74b0d

Observation 85640cdd-56d6-4dc7-bf65-82ecca6b14d4 · inbound

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems cites this paper.

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems Human-Readable Adversarial Prompts: An Investigation into LLM Vulnerabilities Using Situational Context

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-04T17:46:16.097375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:46:16.097375Z digest=sha256:55b402a85f9876663743e0f4ca28fdd0bb5946bd2cf322e0928ef76b3933bf74