5 papers · 1 filter
Navigation World Models
Amir Bar, Gaoyue Zhou, Danny Tran +2
Navigation is a fundamental skill of agents with visual-motor capabilities. We introduce a Navigation World Model (NWM), a controllable video generation model that predicts future…
Vision-Language Models Create Cross-Modal Task Representations
Grace Luo, Trevor Darrell, Amir Bar
Autoregressive vision-language models (VLMs) can handle many tasks within a single model, yet the representations that enable this capability remain opaque. We find that VLMs align…
Revealing and Reducing Gender Biases in Vision and Language Assistants (VLAs)
Leander Girrbach, Stephan Alaniz, Yiran Huang +2
Pre-trained large language models (LLMs) have been reliably integrated with visual input for multimodal tasks. The widespread adoption of instruction-tuned image-to-text vision-lan…
EgoPet: Egomotion and Interaction Data from an Animal's Perspective
Amir Bar, Arya Bakhtiar, Danny Tran +5
Animals perceive the world to plan their actions and interact with other agents to accomplish complex tasks, demonstrating capabilities that are still unmatched by AI systems. To a…
Finding Visual Task Vectors
Alberto Hojel, Yutong Bai, Trevor Darrell +2
Visual Prompting is a technique for teaching models to perform a visual task via in-context examples, without any additional training. In this work, we analyze the activations of M…