research
∙
03/21/2022
The Conceptual VAE
In this report we present a new model of concepts, based on the framewor...
share
research
∙
10/08/2021
lambeq: An Efficient High-Level Python Library for Quantum NLP
We present lambeq, the first high-level Python library for Quantum Natur...
research
∙
09/21/2021
Something Old, Something New: Grammar-based CCG Parsing with Transformer Models
This report describes the parsing problem for Combinatory Categorial Gra...
research
∙
01/13/2021
Formalising Concepts as Grounded Abstractions
The notion of concept has been studied for centuries, by philosophers, l...
research
∙
12/10/2020
Imitating Interactive Intelligence
A common vision from science fiction is that robots will one day inhabit...
research
∙
09/17/2020
Learning to Personalize for Web Search Sessions
The task of session search focuses on using interaction data to improve ...
research
∙
09/03/2020
Grounded Language Learning Fast and Slow
Recent work has shown that large text-based neural language models, trai...
research
∙
06/01/2020
Probing Emergent Semantics in Predictive Agents via Question Answering
Recent work has shown how predictive modeling can endow agents with rich...
research
∙
05/07/2020
Learning to Segment Actions from Observation and Narration
We apply a generative segmental model of task structure, guided by narra...
research
∙
01/16/2020
Who voted for a No Deal Brexit? A Composition Model of Great Britains 2019 European Parliamentary Elections
The purpose of this paper is to use the votes cast at the 2019 European ...
research
∙
10/01/2019
Emergent Systematic Generalization in a Situated Agent
The question of whether deep neural networks are good at generalising be...
research
∙
09/24/2019
Neural Generative Rhetorical Structure Parsing
Rhetorical structure trees have been shown to be useful for several docu...
research
∙
06/14/2019
Scalable Syntax-Aware Language Models Using Knowledge Distillation
Prior work has shown that, on small amounts of training data, syntactic ...
research
∙
06/03/2018
Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing
Latent tree learning models represent sentences by composing their words...
research
∙
04/20/2018
Generating syntactically varied realisations from AMR graphs
Generating from Abstract Meaning Representation (AMR) is an underspecifi...
research
∙
04/11/2018
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
The ability of algorithms to evolve or learn (compositional) communicati...
research
∙
04/11/2018
Emergent Communication through Negotiation
Multi-agent reinforcement learning offers a way to study how communicati...
research
∙
10/26/2017
Understanding Grounded Language Learning Agents
Neural network-based systems can now learn to locate the referents of wo...
research
∙
05/25/2017
Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs
We introduce a neural network that represents sentences by composing the...
research
∙
02/20/2017
Latent Variable Dialogue Models and their Diversity
We present a dialogue generation model that directly captures the variab...
research
∙
10/24/2016
Virtual Embodiment: A Scalable Long-Term Strategy for Artificial Intelligence Research
Meaning has been called the "holy grail" of a variety of scientific disc...
research
∙
11/28/2014
Using Sentence Plausibility to Learn the Semantics of Transitive Verbs
The functional approach to compositional distributional semantics consid...
research
∙
12/31/2010
