This paper presents the Frames dataset (Frames is available at http://datasets.maluuba.com/Frames),
a corpus of 1369 human-human dialogues with an average of 15 turns per …

User simulation is essential for generating enough data to train a statistical spoken dialogue
system. Previous models for user simulation suffer from several drawbacks, such as the …

We introduce TextWorld, a sandbox learning environment for the training and evaluation of
RL agents on text-based games. TextWorld is a Python library that handles interactive play-…

Graph neural networks (GNNs) work well when the graph structure is provided. However,
this structure may not always be available in real-world applications. One solution to this …

Automated metrics such as BLEU are widely used in the machine translation literature. They
have also been used recently in the dialogue community for evaluating dialogue response …

In this paper, we propose to use deep policy networks which are trained with an advantage
actor-critic method for statistically optimised dialogue systems. First, we show that, on …

This paper reports theoretical and empirical results obtained for the score-based Inverse
Reinforcement Learning (IRL) algorithm. It relies on a non-standard setting for IRL consisting of …

Conditional text-to-image generation is an active area of research, with many possible
applications. Existing research has primarily focused on generating a single image from available …

Understanding audio-visual content and the ability to have an informative conversation
about it have both been challenging areas for intelligent systems. The Audio Visual Scene-aware …

Current language generation models suffer from issues such as repetition, incoherence, and
hallucinations. An often-repeated hypothesis is that this brittleness of generation models is …