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.CV2026
Causal World Modeling for Robot Control
Lin Li, Qihang Zhang, Yiming Luo +9
This work highlights that video world modeling, alongside vision-language pre-training, establishes a fresh and independent foundation for robot learning. Intuitively, video world…
cs.LG2025
Polybasic Speculative Decoding Through a Theoretical Perspective
Ruilin Wang, Huixia Li, Yuexiao Ma +4
Inference latency stands as a critical bottleneck in the large-scale deployment of Large Language Models (LLMs). Speculative decoding methods have recently shown promise in acceler…