Authors: Zongjie Li、Daoyuan Wu、Shuai Wang、Zhendong Su Paper: https://arxiv.org/abs/2408.08343 Introduction Large Code Models (LCMs) have shown exceptional performance in various code-related tasks. However, their out-of-the-box performance may not be optimal for all use cases. Supervised Fine-Tuning (SFT) is a critical approach to align these models with specific requirements, enhancing their performance in particular domains. The challenge lies in synthesizing high-quality SFT datasets due to uneven quality and scarcity of domain-specific datasets. Inspired by APIs, which encapsulate rich semantic information in a concise structure, the authors propose DataScope, an API-guided dataset synthesis framework designed to enhance the SFT process for LCMs in…
Read More
