6 papers
User-Feedback-Driven Adaptation for Vision-and-Language Navigation
Yongqiang Yu, Xuhui Li, Hazza Mahmood +6
Real-world deployment of Vision-and-Language Navigation (VLN) agents is constrained by the scarcity of reliable supervision after offline training. While recent adaptation methods…
NavBench: Probing Multimodal Large Language Models for Embodied Navigation
Yanyuan Qiao, Haodong Hong, Wenqi Lyu +5
Multimodal Large Language Models (MLLMs) have demonstrated strong generalization in vision-language tasks, yet their ability to understand and act within embodied environments rema…
Ground-level Viewpoint Vision-and-Language Navigation in Continuous Environments
Zerui Li, Gengze Zhou, Haodong Hong +4
Vision-and-Language Navigation (VLN) empowers agents to associate time-sequenced visual observations with corresponding instructions to make sequential decisions. However, generali…
General Scene Adaptation for Vision-and-Language Navigation
Haodong Hong, Yanyuan Qiao, Sen Wang +2
Vision-and-Language Navigation (VLN) tasks mainly evaluate agents based on one-time execution of individual instructions across multiple environments, aiming to develop agents capa…
Navigating Beyond Instructions: Vision-and-Language Navigation in Obstructed Environments
Haodong Hong, Sen Wang, Zi Huang +2
Real-world navigation often involves dealing with unexpected obstructions such as closed doors, moved objects, and unpredictable entities. However, mainstream Vision-and-Language N…
Why Only Text: Empowering Vision-and-Language Navigation with Multi-modal Prompts
Haodong Hong, Sen Wang, Zi Huang +2
Current Vision-and-Language Navigation (VLN) tasks mainly employ textual instructions to guide agents. However, being inherently abstract, the same textual instruction can be assoc…