106 citations · 160 across the 17 of their papers we have counts for
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cs.LG2024★ 1 cited
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs
Arash Ahmadian, Chris Cremer, Matthias Gallé +5
AI alignment in the shape of Reinforcement Learning from Human Feedback (RLHF) is increasingly treated as a crucial ingredient for high performance large language models. Proximal…
cs.LG2017★ 4 cited
A Maximum Matching Algorithm for Basis Selection in Spectral Learning
Ariadna Quattoni, Xavier Carreras, Matthias Gallé
We present a solution to scale spectral algorithms for learning sequence functions. We are interested in the case where these functions are sparse (that is, for most sequences they…