3 papers
cs.AI2026
FlashRT-PAI: Fast Kernels Are Not Fast Pipelines for Physical AI Inference
Liang Su, David Chen, Jason Li +2
Vision-language-action (VLA), video-action (VA), and world action models (WAMs) form the backbone of modern physical AI systems, yet their real-time single-batch inference remains…
cs.CV2026
TouchScale: 500 Hours of Human Vision and Touch for Visual-Tactile Learning
Dayou Li, Hao Wang, Qianqian Yang +23
Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the contact and pressure that ch…
cs.RO2026
Staircase Policy: Streaming Inference for World-Action Models with Large Action Chunks
Guoheng Sun, Chen Chen, Jin Wang +2
World-Action Models (WAMs) improve robotic manipulation by conditioning action generation on predicted future observations, but future prediction adds further inference overhead to…