Title：Eliciting novel problem solving ability in LLMs: where are we?
Date：2025/11/10 16:30-17:20
Location：R101, CSIE
Speakers：Prof. Khoa D Doan
Host：林軒田教授
Abstract:
LLMs have achieved remarkable performance across many benchmarks, but it remains unclear to what extent they exhibit genuinely novel problem solving and reasoning -- capabilities that are central to scientific discovery, mathematical reasoning, and spatial/cultural reasoning. In this talk, I will present our recent work on probing this question, with a focus on assessing the LLMs in scientific equation discovery and understanding creativity shrinkage in RLVR, a widely used and efficient algorithm for training reasoning LLMs. I will also highlight key challenges in deploying LLMs—and mainstream Machine Learning more broadly—in low-resource settings.
Biography:
Khoa D Doan is currently an Assistant Professor in the College of Engineering and Computer Science (CECS) at Vin University, Vietnam and also the Associated Director of VinUni-Illinois Smart Health Center (VISHC), a joint initiative between VinUniversity and the University of Illinois Urbana-Champaign (UIUC). His research focuses on developing computational frameworks that enable the safe/secure and practical deployment of ML models in constrained and especially low-resource applications. Prior to his academic path, he held multiple industry positions, spanning from software developer to research scientist. He received his Ph.D. in Computer Science (machine learning) from Virginia Tech and his M.S. in Computer Science (high-performance distributed computing) from the University of Maryland, College Park.