R-2R-CE

The 'R2R-CE' dataset/benchmark contains a collection of navigation tasks that evaluate vision-and-language navigation models on their ability to follow natural language instructions in real-world environments.

Papers using R-2R-CE (6)

LatentPilot: Scene-Aware Vision-and-Language Navigation by Dreaming Ahead with Latent Visual Reasoning2026MapDream: Task-Driven Map Learning for Vision-Language Navigation2026Enhancing Vision-Language Navigation with Multimodal Event Knowledge from Real-World Indoor Tour Videos2026Efficient-VLN: A Training-Efficient Vision-Language Navigation Model2025D3D-VLP: Dynamic 3D Vision-Language-Planning Model for Embodied Grounding and Navigation2025SmartWay: Enhanced Waypoint Prediction and Backtracking for Zero-Shot Vision-and-Language Navigation2025