March 19, 2024, 4:54 a.m. | Francesco Taioli, Stefano Rosa, Alberto Castellini, Lorenzo Natale, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Yiming Wang

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.10700v1 Announce Type: cross
Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) is one of the most intuitive yet challenging embodied AI tasks. Agents are tasked to navigate towards a target goal by executing a set of low-level actions, following a series of natural language instructions. All VLN-CE methods in the literature assume that language instructions are exact. However, in practice, instructions given by humans can contain errors when describing a spatial environment due to inaccurate memory or confusion. Current VLN-CE …

arxiv cs.ai cs.cl cs.ro detection error errors language localization mind navigation type vision vision-and-language

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Business Data Analyst

@ Alstom | Johannesburg, GT, ZA