3 papers
cs.CL2026
FewMMBench: A Benchmark for Multimodal Few-Shot Learning
Mustafa Dogan, Ilker Kesen, Iacer Calixto +2
As multimodal large language models (MLLMs) advance in handling interleaved image-text data, assessing their few-shot learning capabilities remains an open challenge. In this paper…
cs.CL2025
Cetvel: A Unified Benchmark for Evaluating Language Understanding, Generation and Cultural Capacity of LLMs for Turkish
Yakup Abrek Er, Ilker Kesen, Gözde Gül Şahin +1
We introduce Cetvel, a comprehensive benchmark designed to evaluate large language models (LLMs) in Turkish. Existing Turkish benchmarks often lack either task diversity or cultura…
cs.CL2025
Multilingual Pretraining for Pixel Language Models
Ilker Kesen, Jonas F. Lotz, Ingo Ziegler +2
Pixel language models operate directly on images of rendered text, eliminating the need for a fixed vocabulary. While these models have demonstrated strong capabilities for downstr…