A greedy token-level Fisher information data selection method that reports improved sample efficiency for GPT-2 supervised fine-tuning on Shakespeare text relative to uniform, density, and AskLLM baselines.
Improved algorithms for linear stochastic bandits
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FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
A greedy token-level Fisher information data selection method that reports improved sample efficiency for GPT-2 supervised fine-tuning on Shakespeare text relative to uniform, density, and AskLLM baselines.