[Imperfect Information Learning Team Seminar] Talk by Prof. Tim Baldwin on Uncertainty Quantification for LLMs

Date/time: 13:30 JST, May 21, 2026

Online Venue: Open to all registered participants. The seminar will be delivered via Zoom. The URL will be provided only to registered participants.

On-site Venue: For RIKEN members only. Open Space at the RIKEN Nihonbashi Office

Title: Uncertainty Quantification for LLMs: From Hallucination Detection to Stronger Reasoning and Agentic AI

Abstract:

In this talk, I will discuss the use of uncertainty quantification in
modulating the expected level of hallucination in large language
models, but also for test-time scaling of LLMs to boost performance at
the cost of additional computation during inference, improving the
quality and efficiency of reasoning in reasoning models, and improving
the efficiency of agentic workflows.

Biosketch:

Tim Baldwin is Provost and Professor of Natural Language Processing at
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), in
addition to being a Melbourne Laureate Professor in the School of
Computing and Information Systems, The University of Melbourne and
Co-founder and Chief Scientist of LibrAI, a start-up focused on AI
safety.

Tim completed a BSc(CS/Maths) and BA(Linguistics/Japanese) at The
University of Melbourne in 1995, and an MEng(CS) and PhD(CS) at the
Tokyo Institute of Technology in 1998 and 2001, respectively. He
joined MBZUAI at the start of 2022, prior to which he was based at The
University of Melbourne for 17 years, and Stanford University for 3
years. His research has been funded by organisations including the
Australian Research Council, Google, Microsoft, Xerox, ByteDance,
SEEK, NTT, and Fujitsu. He is the author of over 500 peer-reviewed
publications across diverse topics in natural language processing and
AI, and the recipient of a number of awards at top NLP conferences.