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20242026
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cs.CL2026

SoS: Analysis of Surface over Semantics in Multilingual Text-To-Image Generation

Carolin Holtermann, Florian Schneider, Anne Lauscher

Text-to-image (T2I) models are increasingly employed by users worldwide. However, prior research has pointed to the high sensitivity of T2I towards particular input languages - whe…

cs.CL2025

GIMMICK -- Globally Inclusive Multimodal Multitask Cultural Knowledge Benchmarking

Florian Schneider, Carolin Holtermann, Chris Biemann +1

Large Vision-Language Models (LVLMs) have recently gained attention due to their distinctive performance and broad applicability. While it has been previously shown that their effi…

cs.CL2025

MVL-SIB: A Massively Multilingual Vision-Language Benchmark for Cross-Modal Topical Matching

Fabian David Schmidt, Florian Schneider, Chris Biemann +1

Existing multilingual vision-language (VL) benchmarks often only cover a handful of languages. Consequently, evaluations of large vision-language models (LVLMs) predominantly targe…

cs.CL2025

Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model

Gregor Geigle, Florian Schneider, Carolin Holtermann +4

Most Large Vision-Language Models (LVLMs) to date are trained predominantly on English data, which makes them struggle to understand non-English input and fail to generate output i…

cs.CL2024

M5 -- A Diverse Benchmark to Assess the Performance of Large Multimodal Models Across Multilingual and Multicultural Vision-Language Tasks

Florian Schneider, Sunayana Sitaram

Since the release of ChatGPT, the field of Natural Language Processing has experienced rapid advancements, particularly in Large Language Models (LLMs) and their multimodal counter…