98 citations · 104 across the 2 of their papers we have counts for
3 papers
cs.CL2024
Chained Tuning Leads to Biased Forgetting
Megan Ung, Alicia Sun, Samuel J. Bell +3
Large language models (LLMs) are often fine-tuned for use on downstream tasks, though this can degrade capabilities learned during previous training. This phenomenon, often referre…
cs.CL2022★ 6 cited
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…
cs.CL2022★ 98 cited
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…