In this report we present a new model of concepts, based on the framewor...
We present lambeq, the first high-level Python library for Quantum Natur...
This report describes the parsing problem for Combinatory Categorial Gra...
The notion of concept has been studied for centuries, by philosophers,
l...
A common vision from science fiction is that robots will one day inhabit...
The task of session search focuses on using interaction data to improve
...
Recent work has shown that large text-based neural language models, trai...
Recent work has shown how predictive modeling can endow agents with rich...
We apply a generative segmental model of task structure, guided by narra...
The purpose of this paper is to use the votes cast at the 2019 European
...
The question of whether deep neural networks are good at generalising be...
Rhetorical structure trees have been shown to be useful for several
docu...
Prior work has shown that, on small amounts of training data, syntactic
...
Latent tree learning models represent sentences by composing their words...
Generating from Abstract Meaning Representation (AMR) is an underspecifi...
The ability of algorithms to evolve or learn (compositional) communicati...
Multi-agent reinforcement learning offers a way to study how communicati...
Neural network-based systems can now learn to locate the referents of wo...
We introduce a neural network that represents sentences by composing the...
We present a dialogue generation model that directly captures the variab...
Meaning has been called the "holy grail" of a variety of scientific
disc...
The functional approach to compositional distributional semantics consid...
Coecke, Sadrzadeh, and Clark (arXiv:1003.4394v1 [cs.CL]) developed a
com...