82 citations · 139 across the 5 of their papers we have counts for
7 papers · 1 filter
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation
Naman Goyal, Cynthia Gao, Vishrav Chaudhary +7
One of the biggest challenges hindering progress in low-resource and multilingual machine translation is the lack of good evaluation benchmarks. Current evaluation benchmarks eithe…
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…
Recipes for Safety in Open-domain Chatbots
Jing Xu, Da Ju, Margaret Li +3
Models trained on large unlabeled corpora of human interactions will learn patterns and mimic behaviors therein, which include offensive or otherwise toxic behavior and unwanted bi…
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…
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…