English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Vision language navigation is the task that requires an agent to navigatethrough a 3D environment based on natural language instructions. One keychallenge in this task is to ground instructions with the current visualinformation that the agent perceives. Most of the existing work employs softattention over individual words to locate the instruction required for the nextaction. However, different words have different functions in a sentence (e.g.,modifiers convey attributes, verbs convey actions). Syntax information likedependencies and phrase structures can aid the agent to locate important partsof the instruction. Hence, in this paper, we propose a navigation agent thatutilizes syntax information derived from a dependency tree to enhance alignmentbetween the instruction and the current visual scenes. Empirically, our agentoutperforms the baseline model that does not use syntax information on theRoom-to-Room dataset, especially in the unseen environment. Besides, our agentachieves the new state-of-the-art on Room-Across-Room dataset, which containsinstructions in 3 languages (English, Hindi, and Telugu). We also show that ouragent is better at aligning instructions with the current visual informationvia qualitative visualizations. Code and models:https://github.com/jialuli-luka/SyntaxVLN

Improving Cross-Modal Alignment in Vision Language Navigation via Syntactic Information