From the 2 of 9 linked papers with an AI index.
5 papers · 1 filter
World Action Models: The Next Frontier in Embodied AI
Siyin Wang, Junhao Shi, Zhaoyang Fu +11
Vision-Language-Action (VLA) models have achieved strong semantic generalization for embodied policy learning, yet they learn reactive observation-to-action mappings without explic…
NavForesee: A Unified Vision-Language World Model for Hierarchical Planning and Dual-Horizon Navigation Prediction
Fei Liu, Shichao Xie, Minghua Luo +4
Embodied navigation for long-horizon tasks, guided by complex natural language instructions, remains a formidable challenge in artificial intelligence. Existing agents often strugg…
ABot-N0: Technical Report on the VLA Foundation Model for Versatile Embodied Navigation
Zedong Chu, Shichao Xie, Xiaolong Wu +41
Embodied navigation has long been fragmented by task-specific architectures. We introduce ABot-N0, a unified Vision-Language-Action (VLA) foundation model that achieves a ``Grand U…
RoboOmni: Proactive Robot Manipulation in Omni-modal Context
Siyin Wang, Jinlan Fu, Feihong Liu +11
Recent advances in Multimodal Large Language Models (MLLMs) have driven rapid progress in Vision-Language-Action (VLA) models for robotic manipulation. Although effective in many s…
Toward Aligning Human and Robot Actions via Multi-Modal Demonstration Learning
Azizul Zahid, Jie Fan, Farong Wang +3
Understanding action correspondence between humans and robots is essential for evaluating alignment in decision-making, particularly in human-robot collaboration and imitation lear…