4 citations · 6 across the 2 of their papers we have counts for
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cs.LG2023★ 4 cited
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
Samyak Jain, Robert Kirk, Ekdeep Singh Lubana +5
Fine-tuning large pre-trained models has become the de facto strategy for developing both task-specific and general-purpose machine learning systems, including developing models th…
cs.LG2023★ 2 cited
Reward Model Ensembles Help Mitigate Overoptimization
Thomas Coste, Usman Anwar, Robert Kirk +1
Reinforcement learning from human feedback (RLHF) is a standard approach for fine-tuning large language models to follow instructions. As part of this process, learned reward model…