CS & CLSP Seminar Series: Rowan Zellers

Description

Rowan Zellers, a final-year PhD candidate at the University of Washington in Computer Science & Engineering, will give a seminar titled "Grounding Language by Seeing, Hearing, and Interacting" for the Computer Science Department and the Center for Language and Speech Processing.

Please attend the event by using the Zoom link.

Abstract:

As humans, our understanding of language is grounded in a rich mental model about "how the world works" – that we learn through perception and interaction. We use this understanding to reason beyond what we literally observe or read, imagining how situations might unfold in the world. Machines today struggle at this kind of reasoning, which limits how they can communicate with humans. In my talk, I will discuss three lines of work to bridge this gap between machines and humans. I will first discuss how we might measure grounded understanding. I will introduce a suite of approaches for constructing benchmarks, using machines in the loop to filter out spurious biases. Next, I will introduce PIGLeT: a model that learns physical commonsense understanding by interacting with the world through simulation, using this knowledge to ground language. From an English-language description of an event, PIGLeT can anticipate how the world state might change – outperforming text-only models that are orders of magnitude larger. Finally, I will introduce MERLOT, which learns about situations in the world by watching millions of YouTube videos with transcribed speech. Through training objectives inspired by the developmental psychology idea of multimodal reentry, MERLOT learns to fuse language, vision, and sound together into powerful representations. Together, these directions suggest a path forward for building machines that learn language rooted in the world.