Follow the Beaten Path: The Role of Route Patterns on Vision-Language Navigation Agents Generalization Abilities

We investigate how route patterns in training environments shape the generalization abilities of Vision-Language Navigation (VLN) agents. Our analysis reveals that agents heavily rely on frequently seen route structures, limiting their ability to navigate in novel environments. We propose insights and directions for building more robust, generalizable VLN agents.

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Deep representation learning: Fundamentals, technologies, applications, and open challenges

A comprehensive survey of deep representation learning covering foundational concepts, core technologies, and diverse real-world applications. We examine the current state of the field across supervised, self-supervised, and unsupervised settings, and identify open challenges that remain for future research.

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