Tarun Tater — accepted AI-conference papers

2025

AbsVis – Benchmarking How Humans and Vision-Language Models “See” Abstract Concepts in Images

Tarun Tater, Diego Frassinelli, Sabine Schulte im Walde

EMNLP 2025

Abstract concepts like mercy and peace often lack clear visual grounding, and thus challenge humans and models to provide suitable image representations. To address this challenge, we introduce AbsVis – a dataset of 675 images annotated with 14,175 concept–explanation attributions from humans and tw

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2024

Unveiling the mystery of visual attributes of concrete and abstract concepts: Variability, nearest neighbors, and challenging categories

Tarun Tater, Sabine Schulte Im Walde, Diego Frassinelli

EMNLP 2024main

The visual representation of a concept varies significantly depending on its meaning and the context where it occurs; this poses multiple challenges both for vision and multimodal models. Our study focuses on concreteness, a well-researched lexical-semantic variable, using it as a case study to exam…

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