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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…
VL-LN Bench: Towards Long-horizon Goal-oriented Navigation with Active Dialogs
Wensi Huang, Shaohao Zhu, Meng Wei +7
In most existing embodied navigation tasks, instructions are well-defined and unambiguous, such as instruction following and object searching. Under this idealized setting, agents…
InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy
Xinyi Chen, Yilun Chen, Yanwei Fu +26
We introduce InternVLA-M1, a unified framework for spatial grounding and robot control that advances instruction-following robots toward scalable, general-purpose intelligence. Its…
InternScenes: A Large-scale Simulatable Indoor Scene Dataset with Realistic Layouts
Weipeng Zhong, Peizhou Cao, Yichen Jin +9
The advancement of Embodied AI heavily relies on large-scale, simulatable 3D scene datasets characterized by scene diversity and realistic layouts. However, existing datasets typic…
InstructVLA: Vision-Language-Action Instruction Tuning from Understanding to Manipulation
Shuai Yang, Hao Li, Bin Wang +7
To operate effectively in the real world, robots should integrate multimodal reasoning with precise action generation. However, existing vision-language-action (VLA) models often s…
Rethinking the Embodied Gap in Vision-and-Language Navigation: A Holistic Study of Physical and Visual Disparities
Liuyi Wang, Xinyuan Xia, Hui Zhao +6
Recent Vision-and-Language Navigation (VLN) advancements are promising, but their idealized assumptions about robot movement and control fail to reflect physically embodied deploym…
StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling
Meng Wei, Chenyang Wan, Xiqian Yu +9
Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low latency grounded in language instruct…
GENMANIP: LLM-driven Simulation for Generalizable Instruction-Following Manipulation
Ning Gao, Yilun Chen, Shuai Yang +7
Robotic manipulation in real-world settings remains challenging, especially regarding robust generalization. Existing simulation platforms lack sufficient support for exploring how…
CronusVLA: Towards Efficient and Robust Manipulation via Multi-Frame Vision-Language-Action Modeling
Hao Li, Shuai Yang, Yilun Chen +8
Recent vision-language-action (VLA) models built on pretrained vision-language models (VLMs) have demonstrated strong performance in robotic manipulation. However, these models rem…
LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agents
Rui Li, Zixuan Hu, Wenxi Qu +13
Scientific embodied agents play a crucial role in modern laboratories by automating complex experimental workflows. Compared to typical household environments, laboratory settings…
TeleOpBench: A Simulator-Centric Benchmark for Dual-Arm Dexterous Teleoperation
Hangyu Li, Qin Zhao, Haoran Xu +10
Teleoperation is a cornerstone of embodied-robot learning, and bimanual dexterous teleoperation in particular provides rich demonstrations that are difficult to obtain with fully a…
NavDP: Learning Sim-to-Real Navigation Diffusion Policy with Privileged Information Guidance
Wenzhe Cai, Jiaqi Peng, Yuqiang Yang +6
Learning to navigate in dynamic and complex open-world environments is a critical yet challenging capability for autonomous robots. Existing approaches often rely on cascaded modul…
Language-to-Space Programming for Training-Free 3D Visual Grounding
Boyu Mi, Hanqing Wang, Tai Wang +2
3D visual grounding (3DVG) is challenging due to the need to understand 3D spatial relations. While supervised approaches have achieved superior performance, they are constrained b…