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2025 EMNLP EMNLP 2025

Evaluating Textual and Visual Semantic Neighborhoods of Abstract and Concrete Concepts

AbstractThis paper presents a systematic evaluation of nearest neighbors across semantic representation spaces in both textual and visual modalities. We focus on nominal concepts with varying concreteness levels, and apply a neighborhood overlap measure to compare these target concepts differing in their linguistic and perceptual nature. We find that alignment is primarily determined by modality, and additionally by level of concreteness: Models from the same modality show stronger alignment than cross-modal models, and spaces of concrete concepts show stronger alignment than those of abstract ones. Overall, larger neighborhood size strengthens the alignment between spaces.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

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