Conveners
Generative and Agentic AI I
- Lav Varshney (Stony Brook University)
-
Tara Sainath (Google)9/11/25, 1:00 PM
End-to-end (E2E) speech recognition has become a popular research paradigm in recent years, allowing the modular components of a conventional speech recognition system (acoustic model, pronunciation model, language model), to be replaced by one neural network. In this talk, we will discuss a multi-year research journey of E2E modeling for speech recognition at Google. This journey started with...
Go to contribution page -
Benji Maruyama (Air Force Research Laboratory)9/11/25, 1:30 PM
AI systems increasingly serve as our knowledge-seeking agents, but how reliably can they discern truth from deception? We investigate a counterintuitive finding: language models equipped with reasoning tools, like metacognitive capabilities, transparency mechanisms, structured deliberation, often perform worse at epistemic tasks than their basic counterparts. Through controlled experiments...
Go to contribution page -
Mengdi Wang (Princeton University)9/11/25, 1:50 PM
Large Language Models (LLMs) are increasingly being explored as tools for scientific reasoning — not just in language tasks, but across disciplines such as math, biology, genomics and physics. In this talk, I’ll discuss recent developments in AI for science, including genome language models, AI co-scientist for biology and quantum physics, and LLMs for math. I’ll highlight both the...
Go to contribution page -
Vivan Amin (Microsoft)9/11/25, 2:10 PM
Embodied AI is rapidly expanding beyond research labs powering intelligent agents in virtual environments and physical robots in the real world. This convergence is redefining how AI perceives, learns, and acts across both simulated and physical domains. In this talk, we will explore the full continuum of Embodied AI: digital agents operating in complex simulations for training, design, and...
Go to contribution page