We present TACO, a family of multi-modal large action models designed to improve performance on complex questions that require multiple capabilities and demand multi-step solutions.
For manufacturers, ecommerce comes with added complexity. Highly technical product details, bulk reorders, and pre-negotiated pricing and entitlements have historically made it difficult to provide cohesive, consumer-like ecommerce experiences for B2B buyers. With…
To address the challenges in generating multimodal instruction data, we developed ProVision, a scalable, programmatic framework that employs scene graphs and human-written programs to systematically synthesize vision-centric instruction data.