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TAMP-Nav aligns embodied navigation with VLMs' 2D capabilities, achieving a 66.2% success rate while drastically improving efficiency.
DAER enables Video-MLLMs to adapt to new domains without sacrificing previously learned knowledge, outperforming traditional methods that struggle with cross-domain interference.
Shifting from explicit domain descriptions to an inductive approach, DOMINO generates high-quality synthetic data that enhances LLM performance without the need for manual prompt engineering.
