4 citations · 10 across the 5 of their papers we have counts for
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cs.CL2023★ 2 cited
SuperHF: Supervised Iterative Learning from Human Feedback
Gabriel Mukobi, Peter Chatain, Su Fong +4
While large language models demonstrate remarkable capabilities, they often present challenges in terms of safety, alignment with human values, and stability during training. Here,…
cs.CL2023★ 4 cited
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models
Mayee F. Chen, Nicholas Roberts, Kush Bhatia +4
The quality of training data impacts the performance of pre-trained large language models (LMs). Given a fixed budget of tokens, we study how to best select data that leads to good…