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cs.LG2025
How Expressive are Knowledge Graph Foundation Models?
Xingyue Huang, Pablo Barceló, Michael M. Bronstein +4
Knowledge Graph Foundation Models (KGFMs) are at the frontier for deep learning on knowledge graphs (KGs), as they can generalize to completely novel knowledge graphs with differen…
cs.LG2025
Ehrenfeucht-Haussler Rank and Chain of Thought
Pablo Barceló, Alexander Kozachinskiy, Tomasz Steifer
The notion of \emph{rank} of a Boolean function has been a cornerstone in PAC learning theory, enabling quasipolynomial-time learning algorithms for polynomial-size decision trees.…
cs.LG2025
Explaining k-Nearest Neighbors: Abductive and Counterfactual Explanations
Pablo Barceló, Alexander Kozachinskiy, Miguel Romero Orth +2
Despite the wide use of -Nearest Neighbors as classification models, their explainability properties remain poorly understood from a theoretical perspective. While nearest neigh…