Video-Native VLMs and Control

We show how image-native vision–language models can be extended to support native video understanding, structured reasoning, tool use, and robotics. Our approach focuses on designing data, modeling, and training recipes to optimize for multimodality input and interaction patterns - treating vision and perception as a first class citizens. We discuss lessons learned from scaling these methods in an open-source model family and their implications for building flexible multimodal systems. Learn more: https://www.perceptron.inc/ About the Speaker Akshat Shrivastava is the CTO and co-founder of Perceptron, previously leading AR On-Device at Meta and conducting research at UW.