9 papers
WALL-SS: Scaling Long-horizon World Models via Next-Scale Autoregression
Maeve Zhang, Rain Sun, Xiang Wang +22
Generative world models provide robots with predictive models of how the world evolves under interaction, with growing potential for simulation, planning, policy evaluation, and ro…
HOST:Robots Acquire Manipulation Skills in Seconds from a Single Human Video
Guangyan Chen, Meiling Wang, Te Cui +9
The ability to acquire skills rapidly and effortlessly while retaining those already mastered is essential for robots. However, current methods still rely on a cumbersome training-…
DMuon: Efficient Distributed Muon Training with Near-Adam Overhead
Vincent Chen, Starrick Liu, Regis Cheng +8
Matrix-orthogonalization-based optimizers, exemplified by Muon, have demonstrated strong convergence behavior across a wide range of modern deep learning workloads. The matrix-awar…
Vesta: A Generalist Embodied Reasoning Model
Johan Bjorck, Zhiqi Li, Yunze Man +29
Robots operating in open-world environments must seamlessly integrate localization, spatial reasoning, navigation, and long-horizon planning. While specialist models excel at indiv…
SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning
Seokju Cho, Ryo Hachiuma, Abhishek Badki +8
Spatial reasoning, the ability to determine where objects are, how they relate, and how they move in 3D, remains a fundamental challenge for vision-language models (VLMs). Tool-aug…
WALL-WM: Carving World Action Modeling at the Event Joints
Shalfun Li, Victor Yao, Charles Yang +29
WALL-WM is a World Action Model that shifts video-action learning from chunk-centric optimization to event-grounded Vision-Language-Action pretraining, using semantically coherent…
Wall-OSS-0.5 Technical Report
Ryan Yu, Pushi Zhang, Starrick Liu +24
Large-scale Vision-Language-Action (VLA) pretraining is increasingly adopted as the foundation for robot policies, yet the evidence for pretrained VLAs is almost invariably reporte…
Mind over Space: Can Multimodal Large Language Models Mentally Navigate?
Qihui Zhu, Shouwei Ruan, Xiao Yang +6
Despite the widespread adoption of MLLMs in embodied agents, their capabilities remain largely confined to reactive planning from immediate observations, consistently failing in sp…
World2Mind: Cognition Toolkit for Allocentric Spatial Reasoning in Foundation Models
Shouwei Ruan, Bin Wang, Zhenyu Wu +4
Achieving robust spatial reasoning remains a fundamental challenge for current Multimodal Foundation Models (MFMs). Existing methods either overfit statistical shortcuts via 3D gro…