Ada-Instruct: Adapting Instruction Generators for Complex Reasoning

• URL: http://arxiv.org/abs/2310.04484v3
• Date: Thu, 03 Oct 2024 15:20:17 GMT
• Title: Ada-Instruct: Adapting Instruction Generators for Complex Reasoning
• Authors: Wanyun Cui, Qianle Wang,
• Abstract summary: We introduce Ada-Instruct, an adaptive instruction generator developed through fine-tuning. We empirically validated Ada-Instruct's efficacy across different applications.
• Score: 14.456571495691561
• License:
• Abstract: Instructions augmentation is a crucial step for unleashing the full potential of large language models (LLMs) in downstream tasks. Existing Self-Instruct methods primarily simulate new instructions from a few initial instructions with in-context learning. However, our study identifies a critical flaw in this approach: even with GPT4o, Self-Instruct cannot generate complex instructions of length $\ge 100$, which is necessary in complex tasks such as code completion. To address this issue, our key insight is that fine-tuning open source LLMs with only ten examples can produce complex instructions that maintain distributional consistency for complex reasoning tasks. We introduce Ada-Instruct, an adaptive instruction generator developed through fine-tuning. We empirically validated Ada-Instruct's efficacy across different applications. The results highlight Ada-Instruct's capacity to generate long, intricate, and distributionally consistent instructions.

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