42 citations · 88 across the 4 of their papers we have counts for
8 papers
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…
Controlling Style in Generated Dialogue
Eric Michael Smith, Diana Gonzalez-Rico, Emily Dinan +1
Open-domain conversation models have become good at generating natural-sounding dialogue, using very large architectures with billions of trainable parameters. The vast training da…
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…
Zero-Shot Fine-Grained Style Transfer: Leveraging Distributed Continuous Style Representations to Transfer To Unseen Styles
Eric Michael Smith, Diana Gonzalez-Rico, Emily Dinan +1
Text style transfer is usually performed using attributes that can take a handful of discrete values (e.g., positive to negative reviews). In this work, we introduce an architectur…