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DreamTraj sets a new benchmark in 6-DoF trajectory prediction by leveraging language and a single image, outperforming traditional methods that rely on privileged inputs.
Decoupling semantic intent from geometric constraints leads to a 47% reduction in physical hallucinations during human-scene interactions.
VLN agents can navigate almost 20% faster in the real world simply by predicting multiple future actions and overlapping execution with perception.
