English

Evaluating Multimodal Representations on Sentence Similarity: vSTS, Visual Semantic Textual Similarity Dataset

Computation and Language 2018-09-12 v1 Artificial Intelligence

Abstract

In this paper we introduce vSTS, a new dataset for measuring textual similarity of sentences using multimodal information. The dataset is comprised by images along with its respectively textual captions. We describe the dataset both quantitatively and qualitatively, and claim that it is a valid gold standard for measuring automatic multimodal textual similarity systems. We also describe the initial experiments combining the multimodal information.

Keywords

Cite

@article{arxiv.1809.03695,
  title  = {Evaluating Multimodal Representations on Sentence Similarity: vSTS, Visual Semantic Textual Similarity Dataset},
  author = {Oier Lopez de Lacalle and Aitor Soroa and Eneko Agirre},
  journal= {arXiv preprint arXiv:1809.03695},
  year   = {2018}
}