98 citations · 161 across the 7 of their papers we have counts for
5 papers · 1 filter
Improving Open Language Models by Learning from Organic Interactions
Jing Xu, Da Ju, Joshua Lane +10
We present BlenderBot 3x, an update on the conversational model BlenderBot 3, which is now trained using organic conversation and feedback data from participating users of the syst…
Multi-Party Chat: Conversational Agents in Group Settings with Humans and Models
Jimmy Wei, Kurt Shuster, Arthur Szlam +3
Current dialogue research primarily studies pairwise (two-party) conversations, and does not address the everyday setting where more than two speakers converse together. In this wo…
Infusing Commonsense World Models with Graph Knowledge
Alexander Gurung, Mojtaba Komeili, Arthur Szlam +2
While language models have become more capable of producing compelling language, we find there are still gaps in maintaining consistency, especially when describing events in a dyn…
Learning New Skills after Deployment: Improving open-domain internet-driven dialogue with human feedback
Jing Xu, Megan Ung, Mojtaba Komeili +3
Frozen models trained to mimic static datasets can never improve their performance. Models that can employ internet-retrieval for up-to-date information and obtain feedback from hu…
BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage
Kurt Shuster, Jing Xu, Mojtaba Komeili +15
We present BlenderBot 3, a 175B parameter dialogue model capable of open-domain conversation with access to the internet and a long-term memory, and having been trained on a large…