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Paper Citation Record · LEDGER

How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2402.13220.

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

pith.paper-citation-record.v1
2402.13220 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:38:17.526542Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:18:56.611300Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4e666fef-e9e3-4a2d-96be-6d1b2539cf5e · inbound

When Data Manipulation Meets Attack Goals: An In-depth Survey of Attacks for VLMs cites this paper.

When Data Manipulation Meets Attack Goals: An In-depth Survey of Attacks for VLMs How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 118

Resolution
unresolved
no resolver link, observed 2026-08-08T15:38:17.526542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:38:17.526542Z digest=sha256:f43d3177416fdcadede8325035fbe22faf82ebe04b029d371b73472f66581963

Observation 7bcdc9fe-4bdc-489f-acd1-84285b85b3ee · inbound

EgoTrigger: Toward Audio-Driven Image Capture for Human Memory Enhancement in All-Day Energy-Efficient Smart Glasses cites this paper.

EgoTrigger: Toward Audio-Driven Image Capture for Human Memory Enhancement in All-Day Energy-Efficient Smart Glasses How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T05:24:14.494907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:24:14.494907Z digest=sha256:a0b5293c597c1bee1ac1c498bef3adb5ab5b373cabd27672f51a261c7812f8fb

Observation cd753afd-ec0b-4db6-ad30-ce52cf740ecd · inbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T20:28:47.627486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:28:47.627486Z digest=sha256:b8dce7ea674e4e411ebe510fad49d90b649f1192ba1ea12169cffa853b4d1d41

Observation b6035dad-8d9a-46f5-901b-c2c4aaf6c4fc · inbound

Exploring and Mitigating Fawning Hallucinations in Large Language Models cites this paper.

Exploring and Mitigating Fawning Hallucinations in Large Language Models How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T13:11:15.327583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:11:15.327583Z digest=sha256:4515da36c743f3d424e739e0d019fc6cbd8d648258fac3a9a111844e12ab27f4

Observation 630c0da0-5cb8-4d2e-86ce-ab3bc5dd05b5 · inbound

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs cites this paper.

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-21T19:54:20.314943Z

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=2026-05-21T19:51:04.983299Z digest=sha256:ed4c5748aafc39c5b9fef6c485f6f8d799712733da61ee6f6702b1eedb90e844

Observation 1e27e445-c6c6-433f-ae16-f9e9b537ec28 · inbound

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs cites this paper.

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-03T21:44:01.397444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:44:01.397444Z digest=sha256:6f11636bff8ccc9df80f3fe519dbe6feae6d87c3889effd1c85ab90d3f8a5ad4

Observation 789829ae-2bbd-4080-ad4c-51a8b11cf0a2 · inbound

MLLMs Get It Right, Then Get It Wrong: Tracing and Correcting Late-Layer Textual Bias cites this paper.

MLLMs Get It Right, Then Get It Wrong: Tracing and Correcting Late-Layer Textual Bias How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:18:56.613130Z

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=2026-06-27T01:28:50.021432Z digest=sha256:33d2e2bf99106c3c0614e94c7869427d9d45f004ac44bacceb375494c73879a6