In recent years, conversational agents (CAs) have become ubiquitous and are a presence in
our daily routines. It seems that the technology has finally ripened to advance the use of CAs …

In recent years, several machine learning models have been proposed. They are trained
with a language modelling objective on large-scale text-only data. With such pretraining …

Robots will eventually be part of every household. It is thus critical to enable algorithms to
learn from and be guided by non-expert users. In this paper, we bring a human in the loop …

Research at the Interaction Lab focuses on human-agent communication using
conversational Natural Language. The ultimate goal is to create systems where humans and …

One-to-one tutoring is often an effective means to help students learn, and recent
experiments with neural conversation systems are promising. However, large open datasets …

Robots will eventually be part of every household. It is thus critical to enable algorithms to
learn from and be guided by non-expert users. In this paper, we bring a human in the loop …

We argue for a new research direction in emergent communication, combining work
onConversational Grounding'with Symbol Grounding (SG+ CG). We first present the fine …

Many task-oriented chatbots and virtual assistants like Siri, Alexa, and Google Assistant are
built as Natural Language (command) Interfaces (NLIs) that allow users to issue natural …

Dialog systems research has primarily been focused around two main types of applications-
task-oriented dialog systems that learn to use clarification to aid in understanding a goal …

Abstract Language Grounding is a fundamental problem in AI, regarding how symbols in
Natural Language (eg words and phrases) refer to aspects of the physical environment (eg …