20 citations · 32 across the 13 of their papers we have counts for
4 papers · 1 filter
Epistemic Artificial Intelligence is Essential for Machine Learning Models to Truly 'Know When They Do Not Know'
Shireen Kudukkil Manchingal, Andrew Bradley, Julian F. P. Kooij +3
Despite AI's impressive achievements, including recent advances in generative and large language models, there remains a significant gap in the ability of AI systems to handle unce…
Proceedings of 1st Workshop on Advancing Artificial Intelligence through Theory of Mind
Mouad Abrini, Omri Abend, Dina Acklin +105
This volume includes a selection of papers presented at the Workshop on Advancing Artificial Intelligence through Theory of Mind held at AAAI 2025 in Philadelphia US on 3rd March 2…
Random-Set Large Language Models
Muhammad Mubashar, Shireen Kudukkil Manchingal, Fabio Cuzzolin
Large Language Models (LLMs) are known to produce very high-quality tests and responses to our queries. But how much can we trust this generated text? In this paper, we study the p…
Generalized Decision Focused Learning under Imprecise Uncertainty--Theoretical Study
Keivan Shariatmadar, Neil Yorke-Smith, Ahmad Osman +3
Decision Focused Learning has emerged as a critical paradigm for integrating machine learning with downstream optimisation. Despite its promise, existing methodologies predominantl…