10 Open Challenges Steering the Future of Vision-Language-Action Models
Authors: name: Soujanya Poria, name: Navonil Majumder, name: Chia-Yu Hung, name: Amir Ali Bagherzadeh, name: Chuan Li, name: Kenneth Kwok, name: Ziwei Wang, name: Cheston Tan, name: Jiajun Wu, name: David Hsu
Organization: Deep Cognition and Language Research (DeCLaRe) Lab

Due to their ability of follow natural language instructions,
vision-language-action (VLA) models are increasingly prevalent in the embodied
AI arena, following the widespread success of their precursors -- LLMs and
VLMs. In this paper, we discuss 10 principal milestones in the ongoing
development of VLA models -- multimodality, reasoning, data, evaluation,
cross-robot action generalization, efficiency, whole-body coordination, safety,
agents, and coordination with humans. Furthermore, we discuss the emerging
trends of using spatial understanding, modeling world dynamics, post training,
and data synthesis -- all aiming to reach these milestones. Through these
discussions, we hope to bring attention to the research avenues that may
accelerate the development of VLA models into wider acceptability.