Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.13220.
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
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T05:24:14.494907Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T20:18:56.611300Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 7bcdc9fe-4bdc-489f-acd1-84285b85b3ee · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd753afd-ec0b-4db6-ad30-ce52cf740ecd · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b6035dad-8d9a-46f5-901b-c2c4aaf6c4fc · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 630c0da0-5cb8-4d2e-86ce-ab3bc5dd05b5 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1e27e445-c6c6-433f-ae16-f9e9b537ec28 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 789829ae-2bbd-4080-ad4c-51a8b11cf0a2 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.