Can 3D Vision-Language Models Truly Understand Natural Language?

arXiv:2403.14760v1 Announce Type: new
Abstract: Rapid advancements in 3D vision-language (3D-VL) tasks have opened up new avenues for human interaction with embodied agents or robots using natural language. Despite this progress, we find a notable limitation: existing 3D-VL models exhibit sensitivity to the styles of language input, struggling to understand sentences with the same semantic meaning but written in different variants. This observation raises a critical question: Can 3D vision-language models truly understand natural language? To test the language understandability …

abstract agents arxiv cs.cv embodied human language language models natural natural language progress robots sensitivity tasks type vision vision-language models