JINDONG WANG: Thank you. Nice to be here. STEVEN EUIJONG WHANG: It’s great to be here. HUIZINGA: So, Jindong, I’ll start with you. In just a few sentences, tell us what problem your research addresses and why people should care about it. JINDONG WANG: OK, everybody knows that with the widespread usage of large language models, hallucination has become a crucial factor of concern. Hallucination occurs when models generate false or nonexistent information. In particular, factual hallucination greatly undermines the […]

WEIZHU CHEN: Thank you for having me, Amber.  TINGLE: So let’s start with a brief overview of your paper. In a couple sentences, tell us about the problem your research addresses and, more importantly, why the research community and beyond should know about this work.  CHEN: So my team basically in Microsoft GenAI, we are working on model training. So one of the things actually we do in the pretraining, we realize the importance of the data. And we found […]

PRANJAL CHITALE: Hi, Gretchen. Thanks for having me. HUIZINGA: So, Pranjal, give us an overview of this paper. In a couple sentences, what problem are you trying to solve, and why should people care about it? CHITALE: So we are witnessing some exciting times as LLMs are rapidly evolving as tools for countless use cases. While most of these LLMs were initially leveraged for natural language processing tasks, they are now expanded across languages and modalities. However, a major gap […]

DYLAN FOSTER: Thanks for having me. TINGLE: Let’s start with a brief overview of this paper. Tell us about the problem this work addresses and why the research community should know about it. FOSTER: So this is a, kind of, a theoretical work on reinforcement learning, or RL. When I say reinforcement learning, broadly speaking, this is talking about the question of how can we design AI agents that are capable of, like, interacting with unknown environments and learning how […]