A new testing framework for VLN agents combines adaptive test case generation, capability oracles, and feedback to discover more failures and attribute them to specific capability deficiencies more accurately than baselines.
Olivia-nav: An online lifelong vision language approach for mobile robot social navigation
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AutoSpatial improves VLM spatial reasoning for social navigation by combining minimal manual supervision with auto-labeled VQA pairs and hierarchical training, showing gains up to 20.5% in action prediction over baselines.
citing papers explorer
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Where Did It Go Wrong? Capability-Oriented Failure Attribution for Vision-and-Language Navigation Agents
A new testing framework for VLN agents combines adaptive test case generation, capability oracles, and feedback to discover more failures and attribute them to specific capability deficiencies more accurately than baselines.
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AutoSpatial: Visual-Language Reasoning for Social Robot Navigation through Efficient Spatial Reasoning Learning
AutoSpatial improves VLM spatial reasoning for social navigation by combining minimal manual supervision with auto-labeled VQA pairs and hierarchical training, showing gains up to 20.5% in action prediction over baselines.