Zied Bouraoui (University of Artois – CRIL, CNRS) will run a Seminar@SystemX on the topic “Learning Conceptual Representations from Language Models”, on March 20, 2025, from 2:00pm to 3:00pm.

>> Connect to the webinar <<

Resume

Capturing the semantic meaning of concepts in static vector representations remains a key challenge in applications that require word meaning to be modeled without contextual information. Static embeddings are essential for tasks such as zero-shot image classification, zero-shot entity typing, ontology alignment and completion, taxonomy learning, and query representation in information retrieval systems. In this talk, I will explore strategies for learning effective concept and relation representations from language models and provide an overview of how these embeddings can enhance downstream applications.

Biography

Zied Bouraoui is a professor of Computer Science at the University of Artois and a researcher at CRIL (CNRS UMR 8188). His primary research interests include commonsense reasoning, reasoning with imperfect information, and natural language processing. He has co-authored over 40 peer-reviewed papers published in top-tier AI journals and conferences (e.g., AAAI, IJCAI, KRR, ACL, SIGIR, EMNLP), many of which have received awards at prestigious conferences. His research is supported by several projects, including the Chair IA Be4musIA, ANR JCJC ERIANA (2023-2027), ANR VIVAH (2020-2025), and the European H2020 ICT-48 Trustworthy AI program.

 

Registration



- SUBSCRIPTION NEWSLETTER

Subscribe to IRT SystemX's
newsletter

and receive every month the latest news from the institute: