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Exploring the Mystery of Influential Data for Mathematical Reasoning
April 2, 2024, 7:52 p.m. | Xinzhe Ni, Yeyun Gong, Zhibin Gou, Yelong Shen, Yujiu Yang, Nan Duan, Weizhu Chen
cs.CL updates on arXiv.org arxiv.org
Abstract: Selecting influential data for fine-tuning on downstream tasks is a key factor for both performance and computation efficiency. Recent works have shown that training with only limited data can show a superior performance on general tasks. However, the feasibility on mathematical reasoning tasks has not been validated. To go further, there exist two open questions for mathematical reasoning: how to select influential data and what is an influential data composition. For the former one, we …
abstract arxiv computation cs.cl data efficiency fine-tuning general however key mathematical reasoning performance reasoning show tasks training type
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