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cs.CL2024
PersonaMath: Boosting Mathematical Reasoning via Persona-Driven Data Augmentation
Jing Luo, Longze Chen, Run Luo +12
While closed-source Large Language Models (LLMs) demonstrate strong mathematical problem-solving abilities, open-source models still face challenges with such tasks. To bridge this…
cs.CL2024
Ruler: A Model-Agnostic Method to Control Generated Length for Large Language Models
Jiaming Li, Lei Zhang, Yunshui Li +5
The instruction-following ability of large language models enables humans to interact with AI agents in a natural way. However, when required to generate responses of a specific le…