Papers

Filtered to spatial reasoning · clear filter

Browse by term

continual learning 64reinforcement learning 34large language models 17benchmarking 12vision-language models 10generative models 8language models 8video generation 7multimodal models 6natural language processing 6robotics 6world models 6benchmarks 5diffusion models 5on-policy distillation 5policy optimization 5scalability 5self-distillation 5vision-language-action models 5autoregressive models 4computer vision 4diffusion transformers 4LLMs 4multimodal large language models 4verifiable rewards 4attention mechanisms 3embodied intelligence 3image editing 3long-term memory 3multimodal learning 3

Matching papers

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model

32 upvotes · 20 JUL 2026 · Kehan Li, Bohan Hou, Minghao Zhu et al.

This paper introduces RynnBrain 1.1, a family of large-scale embodied foundation models that can perform tasks like spatial reasoning, localization, and planning, and shows promising results in real-world robot experiments. Practitioners may care about the potential of these models for robot manipulation and control.

embodied foundation modelsphysically grounded frameworksspatial reasoningrobot manipulation3D groundingreal-robot experiments

SpatialCLI: Learning to Reason With Spatial Tools, Then Without Them

21 upvotes · 30 JUL 2026 · Yang Zhou, Zixuan Huang, Sunzhu Li et al.

This paper develops a framework, SpatialCLI, to help vision-language models (VLMs) better understand and use visual tools to make better decisions. By training VLMs to reason with spatial tools and then internalize those capabilities, SpatialCLI can improve the performance of VLMs in tasks that require visual reasoning.

vision-language modelsspatial reasoningvisual perceptionembodied agentsreinforcement learning