3 papers
cs.CV2026
Reflective VLA: In-Context Action Consequences Make VLAs Generalize
Qing Lian, Kent Yu, Lei Zhang
Most vision-language-action (VLA) models are reactive: they predict the next action from the current instruction and observation, implicitly assuming that the current observation f…
cs.RO2026
Guide, Think, Act: Interactive Embodied Reasoning in Vision-Language-Action Models
Yiran Ling, Qing Lian, Jinghang Li +6
In this paper, we propose GTA-VLA(Guide, Think, Act), an interactive Vision-Language-Action (VLA) framework that enables spatially steerable embodied reasoning by allowing users to…
cs.AI2026
MAP: A Map-then-Act Paradigm for Long-Horizon Interactive Agent Reasoning
Yuxin Liu, Ziang Ye, Yueqing Sun +6
Current interactive LLM agents rely on goal-conditioned stepwise planning, where environmental understanding is acquired reactively during execution rather than established beforeh…