LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts'intent into tool invocations. However, existing evaluations focus on knowledge-based assessments or end-to-end agentic tasks, and do not directly measure LLMs'ability to generate executable commands for real-world cy...
Peng-Fei Li, Naufal Suryanto, Si-Cheng Zhang et al.· 0 citations
Multi-Resolution Pyramid Transformer (MRPT) is introduced, a model that hierarchically aggregates multi-resolution information from cellular to tissue and WSI levels and surpasses recent foundation models and Multimodal Large Language Models in cancer subtype classification, tissue phenotyping, and Visual Question Answ...
B. Alawode, Moshira Abdalla, Dwarikanath Mahapatra et al.· 0 citations
SAFIRE is introduced, a large-scale benchmark for fire-smoke understanding in MLLMs, comprising 83K captioned images from 20 scenarios and 193K multiple-choice VQA (MCVQA) generated from a 9.7K-image subset, spanning 10 evaluation dimensions from basic perception to higher-order reasoning.
Peng-Fei Li, Naufal Suryanto, Si-Cheng Zhang et al.· 0 citations
Text-to-image (T2I) generation has achieved remarkable progress in recent years. However, existing research has largely focused on English-only settings, leaving cross-lingual performance gaps and language-specific effects insufficiently explored. To fill this gap, we introduce LingT2I, a benchmark covering 10 widely u...
Si-Cheng Zhang, Zhong-Hao Yan, Bin-Zhu Xie et al.· 0 citations
This work introduces ReACT-CLIP, a response-conditioned test-time defense that separately determines how strongly each input should be corrected and whether defensive intervention is necessary, and quantifies this variation using a prediction-instability score computed by Jensen--Shannon divergence and combines it with...
H. Malik, Toluwani Aremu, Samuele Poppi et al.· 0 citations
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