causal pretraining 1foundation models 1robot control 1sparse mixture of experts 1video-action models 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.RO2026
Native Video-Action Pretraining for Generalizable Robot Control
Qihang Zhang, Lin Li, Luyao Zhang +26
The paper introduces LingBot-VA 2.0, a video-action foundation model designed specifically for robot control, featuring a semantic visual-action tokenizer, causal pretraining, a sp…
cs.RO2026
Real2Edit2Real: Generating Robotic Demonstrations via a 3D Control Interface
Yujie Zhao, Hongwei Fan, Di Chen +5
Recent progress in robot learning has been driven by large-scale datasets and powerful visuomotor policy architectures, yet policy robustness remains limited by the substantial cos…
cs.RO2025
TwinAligner: Visual-Dynamic Alignment Empowers Physics-aware Real2Sim2Real for Robotic Manipulation
Hongwei Fan, Hang Dai, Jiyao Zhang +7
The robotics field is evolving towards data-driven, end-to-end learning, inspired by multimodal large models. However, reliance on expensive real-world data limits progress. Simula…