Speaker: Jacek Mańdziuk
Title: Successes and Limitations of Artificial Intelligence in Abstract Visual Reasoning
Time: 9:30 AM, September 26, 2025(Friday)
Location:290 Arts and Science Building
Abstract:
Abstract Visual Reasoning (AVR) involves a suite of tasks that require the ability to discover common concepts underlying the set of images through an analogy-making process, similar to how humans solve IQ tests. This talk will summarize the main types of AVR problems along with possible solution approaches. In the second part of the talk, it will delve into Bongard Problems (BPs) which pose a fundamental AVR challenge, mainly due to the requirement to combine visual reasoning with verbal description. In particular, a question will be posed as to whether multimodal large language models (MLLMs), inherently designed to combine vision and language, are capable of tackling BPs. To answer this question, the results of applying state-of-the-art MLLMs to solving BPs (composed of either synthetic or real-world images) will be presented and analysed, revealing significant AVR limitations of contemporary models.
Personal Introduction:
Prof. Jacek Mańdziuk, Ph.D., D.Sc., is a full professor at the Faculty of Mathematics and Information Science, Warsaw University of Technology, and Head of Division of Artificial Intelligence and Computational Methods. He is also a full research professor of the AGH University of Krakow.He is an IEEE Senior Member and was General Co-Chair of the 2021 IEEE Congress on Evolutionary Computation, Krakow, Poland, and Chair of the annual IEEE SSCI Symposium on Computational Intelligence for Human-like Intelligence 2013- 2023. He is a recipient of the Fulbright Senior Research Award (UC Berkeley and ICSI Berkeley, USA) and the Robert Schuman Foundation Fellowship (CNRS, Besancon, France). He is a Founding Chair of the IEEE ETTC Task Force on TowardHuman-like Intelligence. He presented his research at numerous invited conference and university talks worldwide. He has published 3 books and over 200 research papers, many in leading journals and top-tier conferences on artificial intelligence and machine learning. This year he was elected a Member of the Polish Academy of Sciences.His research interests include application of computational intelligence and artificial intelligence methods to dynamic and bilevel optimization problems, abstract visual reasoning, games, and human-machine cooperation. He is also interested in the development of human-like learning and problem-solving methods.
[Editor:Sijia Wang]