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cs.CV2026
A Systematic Study of Cross-Modal Typographic Attacks on Audio-Visual Reasoning
Tianle Chen, Deepti Ghadiyaram
As audio-visual multi-modal large language models (MLLMs) are increasingly deployed in safety-critical applications, understanding their cross-modal vulnerabilities is essential. T…
cs.CV2026
VLM-UQBench: A Benchmark for Modality-Specific and Cross-Modality Uncertainties in Vision Language Models
Chenyu Wang, Tianle Chen, H. M. Sabbir Ahmad +2
Uncertainty quantification (UQ) is vital for ensuring that vision-language models (VLMs) behave safely and reliably. A central challenge is to localize uncertainty to its source, d…