IDEA is a TTA framework for VLN that builds a dynamic asset library from Fisher-weighted soft prompts and domain coordinates, then uses convex-hull projection for cross-domain bridging and training-free adaptation.
Wmnav: Integrating vision-language models into world models for object goal navigation
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OVAL introduces an open-vocabulary memory model with structured descriptors and multi-value frontier scoring to enable efficient lifelong object goal navigation in unseen settings.
FSUNav's dual brain-inspired modules achieve state-of-the-art zero-shot goal navigation across heterogeneous robots with improved speed, safety, and generalization.
FiLM-Nav fine-tunes VLMs on a mixture of simulated navigation tasks to reach state-of-the-art SPL and success on HM3D ObjectNav and OVON benchmarks with generalization to unseen categories.
citing papers explorer
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Turning Adaptation into Assets: Cross-Domain Bridging for Online Vision-Language Navigation
IDEA is a TTA framework for VLN that builds a dynamic asset library from Fisher-weighted soft prompts and domain coordinates, then uses convex-hull projection for cross-domain bridging and training-free adaptation.
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OVAL: Open-Vocabulary Augmented Memory Model for Lifelong Object Goal Navigation
OVAL introduces an open-vocabulary memory model with structured descriptors and multi-value frontier scoring to enable efficient lifelong object goal navigation in unseen settings.
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FSUNav: A Cerebrum-Cerebellum Architecture for Fast, Safe, and Universal Zero-Shot Goal-Oriented Navigation
FSUNav's dual brain-inspired modules achieve state-of-the-art zero-shot goal navigation across heterogeneous robots with improved speed, safety, and generalization.
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FiLM-Nav: Efficient and Generalizable Navigation via VLM Fine-tuning
FiLM-Nav fine-tunes VLMs on a mixture of simulated navigation tasks to reach state-of-the-art SPL and success on HM3D ObjectNav and OVON benchmarks with generalization to unseen categories.