Cross-Modal Taxonomic Generalization in (Vision-) Language Models
What is the interplay between semantic representations learned by language models (LM) from surface form alone to those learned from more grounded evidence? We study this question for a scenario where part of the input comes from a different modality -- in our case, in a vision-language model (VLM), where a pretrained LM is aligned with a pretrained image encoder. As a case study, we focus on the task of predicting hypernyms of objects represented in images. We do so in a VLM setup where the image encoder and LM are kept frozen, and only the intermediate mappings are learned. We progressively deprive the VLM of explicit evidence for hypernyms, and test whether knowledge of hypernyms is re...
| Authors | Tianyang Xu, Marcelo Sandoval-Castaneda, Karen Livescu et al. |
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| Primary category | cs.CL |
| Published | 8 March 2026 |
| Last updated at source | 22 April 2026 |
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