StereoNav reaches new benchmark highs on R2R-CE and RxR-CE and improves real-robot reliability by supplying persistent target-location priors and stereo-derived geometry that stay stable under lighting changes and blur.
Let’s reward step-by-step: Step-aware con- trastive alignment for vision-language navigation in continuous environments
2 Pith papers cite this work. Polarity classification is still indexing.
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LiveVLN enables smoother vision-language navigation by overlapping action execution with ongoing observation processing, preserving benchmark scores while cutting real-world waiting time by up to 77.7 percent.
citing papers explorer
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What Limits Vision-and-Language Navigation ?
StereoNav reaches new benchmark highs on R2R-CE and RxR-CE and improves real-robot reliability by supplying persistent target-location priors and stereo-derived geometry that stay stable under lighting changes and blur.
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LiveVLN: Breaking the Stop-and-Go Loop in Vision-Language Navigation
LiveVLN enables smoother vision-language navigation by overlapping action execution with ongoing observation processing, preserving benchmark scores while cutting real-world waiting time by up to 77.7 percent.