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Mirella Lapata
The University of Edinburgh
Title: 
Prompting is *not* all you need! Or why Multi-LLM Collaboration Matters
Summary: 

Recent years have witnessed the rise of increasingly larger and more sophisticated language models (LMs) capable of performing every task imaginable, sometimes at (super)human level. In this talk, I will argue that in many realistic scenarios solely relying on a single general-purpose LLM is suboptimal. A single LLM is likely to under-represent real-world data distributions, heterogeneous skills, and task-specific requirements. Instead, I will discuss Multi-LLM collaboration as an alternative for compositional generative modeling. This approach leads to more effective problem-solving while being more inclusive and explainable. I will focus on narrative story generation tasks and demonstrate how these can be tackled by orchestrating a society of agents --- each pursuing individual goals while collectively working toward the overall task objective. Additionally, I will explore how these agent societies leverage reasoning to improve performance.</div>

Bio: 
Mirella Lapata is professor of natural language processing in the School of Informatics at the University of Edinburgh. Her research focuses on getting computers to understand, reason with, and generate natural language. She is the first recipient (2009) of the British Computer Society and Information Retrieval Specialist Group (BCS/IRSG) Karen Sparck Jones award and a Fellow of the Royal Society of Edinburgh, the ACL, and Academia Europaea.
Mirella has also received best paper awards in leading NLP conferences and has served on the editorial boards of the Journal of Artificial Intelligence Research, the Transactions of the ACL, and Computational Linguistics. She was president of SIGDAT (the group that organizes EMNLP) in 2018. She has been awarded an ERC consolidator grant, a Royal Society Wolfson Research Merit Award, and a UKRI Turing AI World-Leading Researcher Fellowship.
Thursday, June 5, 2025 - 15:00

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