4 papers
Semantic Intelligence Against CSAM: The PreventCSA@EU Ontology Framework for Classification and Investigation
Elias Tzortzakakis, Emmanouela Kokolaki, Evangelia Daskalaki +1
This work presents the PreventCSA@EU ontology, a semantically grounded framework designed to support the identification, classification, annotation, and analysis of online Child Se…
SABRE: Scalable and Automated Benchmarking of VLMs under Stress
Zixuan Lan, Luzhe Sun, Matthew R. Walter +1
Vision-language models (VLMs) are improving rapidly, but benchmark development lags behind, making weaknesses hard to identify. Building stress tests is costly: samples must satisf…
Seeing without Looking: Do Vision-Language Benchmarks Really Test Vision?
Zixuan Lan, Luzhe Sun, Matthew R. Walter +1
Benchmark accuracy is often implicitly assumed to reflect grounded visual understanding in vision-language models (VLMs), yet it remains unclear to what extent such scores truly re…
Text or Pixels? It Takes Half: On the Token Efficiency of Visual Text Inputs in Multimodal LLMs
Yanhong Li, Zixuan Lan, Jiawei Zhou
Large language models (LLMs) and their multimodal variants can now process visual inputs, including images of text. This raises an intriguing question: can we compress textual inpu…