The DOI matches its Crossref record.
NaVILA: Legged Robot Vision-Language-Action Model for Navigation
Open accessAbstract
https://navila-bot.github
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Large-scale vision-language-action models incur significant computational overhead, restrict action generation frequency, and fundamentally lack mechanisms for persistent, structured spatial memory integration.
“However, these large-scale models incur significant computational overhead, restrict action generation frequency, and fundamentally lack mechanisms for persistent, structured spatial memory integration.”
From Brain-inspired spatial intelligence for embodied agents (2026) · cites this paper as [85]
The Introduction describes the VLA as a large, computationally intensive model that runs at a lower frequency, supporting the overhead and action-frequency points. The Method section does not establish that these models fundamentally lack persistent, structured spatial memory integration; it instead describes historical frames used as a memory bank. No page numbers are available in our copy. (LLM, conf=0.88)
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Brain-inspired spatial intelligence for embodied agents
Ruan, S., Wang, L., Kang, C., Zhu, Q., Liu, S., Wei, X., & Su, H. (2026) · Nature Communications · doi:10.1038/s41467-026-74358-5 · Cited by 1
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Metadata
- Authors
- Cheng, A.-C., Ji, Y., Yang, Z., Gongye, Z., Zou, X., Kautz, J., Biyik, E., Yin, H., Liu, S., & Wang, X.
- Affiliations
- Nvidia (United Kingdom) (GB)
- University of California San Diego (US)
- University of Southern California (US)
- Venue
- Robotics: Science and Systems XXI
- Published
- 2025-06-21
- OpenAlex
- W4414050442
- Cited by
- 54
- References
- 0
- Citations by year
- 2026: 43 · 2025: 11
- FWCI
- 40.81
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Robotics: Science and Systems (publishedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by)
- arXiv (Cornell University) (cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Locomotion and Control
- Keywords
- legged robots, robot navigation, vision-language-action models, robot vision, robot control, embodied AI
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