activity
20182020
most citedOpen-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions

42 citations · 49 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CL2020

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…

cs.CL202042 cited

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…

cs.CL2020

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…

cs.CL20207 cited

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…

cs.CL2019

The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents

Kurt Shuster, Da Ju, Stephen Roller +3

We introduce dodecaDialogue: a set of 12 tasks that measures if a conversational agent can communicate engagingly with personality and empathy, ask questions, answer questions by u…

cs.LG2018

High-Level Strategy Selection under Partial Observability in StarCraft: Brood War

Jonas Gehring, Da Ju, Vegard Mella +3

We consider the problem of high-level strategy selection in the adversarial setting of real-time strategy games from a reinforcement learning perspective, where taking an action co…