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@omarsar0

Number Understanding of LLMs Provides a comprehensive analysis of the numerical understanding and processing ability (NUPA) of LLMs. Findings from the paper: - naive finetuning can improve NUPA a lot on many but not all tasks - techniques designed to enhance NUPA prove ineffective for finetuning pretrained models It also explores chain-of-thought techniques applied to NUPA and suggests that chain-of-thought methods face scalability challenges, making them difficult to apply in practical scenarios.

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