AIGeN: An Adversarial Approach for Instruction Generation in VLN

arXiv:2404.10054v1 Announce Type: cross
Abstract: In the last few years, the research interest in Vision-and-Language Navigation (VLN) has grown significantly. VLN is a challenging task that involves an agent following human instructions and navigating in a previously unknown environment to reach a specified goal. Recent work in literature focuses on different ways to augment the available datasets of instructions for improving navigation performance by exploiting synthetic training data. In this work, we propose AIGeN, a novel architecture inspired by Generative …

abstract adversarial agent arxiv cs.ai cs.cl cs.cv cs.ro environment human language literature navigation research type vision vision-and-language work