623 citations · 1.1k across the 25 of their papers we have counts for
6 papers · 1 filter
Multi-Modal Open-Domain Dialogue
Kurt Shuster, Eric Michael Smith, Da Ju +1
Recent work in open-domain conversational agents has demonstrated that significant improvements in model engagingness and humanness metrics can be achieved via massive scaling in b…
Deploying Lifelong Open-Domain Dialogue Learning
Kurt Shuster, Jack Urbanek, Emily Dinan +2
Much of NLP research has focused on crowdsourced static datasets and the supervised learning paradigm of training once and then evaluating test performance. As argued in de Vries e…
Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions
Stephen Roller, Y-Lan Boureau, Jason Weston +13
We present our view of what is necessary to build an engaging open-domain conversational agent: covering the qualities of such an agent, the pieces of the puzzle that have been bui…
Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal +9
Building open-domain chatbots is a challenging area for machine learning research. While prior work has shown that scaling neural models in the number of parameters and the size of…
Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills
Eric Michael Smith, Mary Williamson, Kurt Shuster +2
Being engaging, knowledgeable, and empathetic are all desirable general qualities in a conversational agent. Previous work has introduced tasks and datasets that aim to help agents…
All-in-One Image-Grounded Conversational Agents
Da Ju, Kurt Shuster, Y-Lan Boureau +1
As single-task accuracy on individual language and image tasks has improved substantially in the last few years, the long-term goal of a generally skilled agent that can both see a…