2 papers
cs.LG2025
Compositionality Unlocks Deep Interpretable Models
Thomas Dooms, Ward Gauderis, Geraint A. Wiggins +1
We propose -net, an intrinsically interpretable architecture combining the compositional multilinear structure of tensor networks with the expressivity and efficiency of deep n…
cs.CL2025
Quantum Methods for Managing Ambiguity in Natural Language Processing
Jurek Eisinger, Ward Gauderis, Lin de Huybrecht +1
The Categorical Compositional Distributional (DisCoCat) framework models meaning in natural language using the mathematical framework of quantum theory, expressed as formal diagram…