Language-Aligned Waypoint (LAW) Supervision for Vision-and-Language Navigation in Continuous Environments

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Abstract

In the Vision-and-Language Navigation (VLN) task an embodied agent navigates a 3D environment, following natural language instructions. A challenge in this task is how to handle 'off the path' scenarios where an agent veers from a reference path. Prior work supervises the agent with actions based on the shortest path from the agent's location to the goal, but such goal-oriented supervision is often not in alignment with the instruction. Furthermore, the evaluation metrics employed by prior work do not measure how much of a language instruction the agent is able to follow. In this work, we propose a simple and effective language-aligned supervision scheme, and a new metric that measures the number of sub-instructions the agent has completed during navigation.

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APA

Raychaudhuri, S., Wani, S., Patel, S., Jain, U., & Chang, A. X. (2021). Language-Aligned Waypoint (LAW) Supervision for Vision-and-Language Navigation in Continuous Environments. In EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 4018–4028). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.emnlp-main.328

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