From the 1 of 11 linked papers with an AI index.
11 papers
Embodied Agents Take Control: Minimal-Interface Zero-Shot Agents Rival Industrial-Scale Policies in Vision-and-Language Navigation
Jian Zhou, Xunyi Zhao, Gengze Zhou +4
The paper investigates using general-purpose language models as autonomous embodied agents for zero-shot vision-and-language navigation, showing that with only a monocular RGB came…
Ask When It Pays: Cost-Aware Open-Ended Interaction for Instance Goal Navigation
Xunyi Zhao, Sihao Lin, Gengze Zhou +5
Instance Goal Navigation (IGN) requires an embodied agent to find a specific object instance among distractors from an under-specified natural-language description. Such ambiguity…
SpatialAnt: Autonomous Zero-Shot Robot Navigation via Active Scene Reconstruction and Visual Anticipation
Jiwen Zhang, Xiangyu Shi, Siyuan Wang +3
Vision-and-Language Navigation (VLN) has recently benefited from Multimodal Large Language Models (MLLMs), enabling zero-shot navigation. While recent exploration-based zero-shot m…
Decoupled Action Expert: Confining Task Knowledge to the Conditioning Pathway
Jian Zhou, Sihao Lin, Shuai Fu +3
Many recent Vision-Language-Action models employ diffusion or flow-matching backbones with hundreds of millions of parameters for action generation. However, unlike image synthesis…
One Agent to Guide Them All: Empowering MLLMs for Vision-and-Language Navigation via Explicit World Representation
Zerui Li, Hongpei Zheng, Fangguo Zhao +5
A navigable agent needs to understand both high-level semantic instructions and precise spatial perceptions. Building navigation agents centered on Multimodal Large Language Models…
VLNVerse: A Benchmark for Vision-Language Navigation with Versatile, Embodied, Realistic Simulation and Evaluation
Sihao Lin, Zerui Li, Xunyi Zhao +10
Despite remarkable progress in Vision-Language Navigation (VLN), existing benchmarks remain confined to fixed, small-scale datasets with naive physical simulation. These shortcomin…