4 papers
Scaling Laws for Code: A More Data-Hungry Regime
Xianzhen Luo, Wenzhen Zheng, Qingfu Zhu +5
Code Large Language Models (LLMs) are revolutionizing software engineering. However, scaling laws that guide the efficient training are predominantly analyzed on Natural Language (…
Is Compression Really Linear with Code Intelligence?
Shijie Xuyang, Xianzhen Luo, Zheng Chu +6
Understanding the relationship between data compression and the capabilities of Large Language Models (LLMs) is crucial, especially in specialized domains like code intelligence. P…
Probing How Scalable Table Data Enhances General Long-Context Reasoning
Huaibing Xie, Guoliang Zhao, Yang Liu +8
As real-world tasks grow increasingly complex, long-context reasoning has become a core capability for Large Language Models (LLMs). However, few studies explore which data types a…
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Siming Huang, Tianhao Cheng, J. K. Liu +16
Large language models (LLMs) for code have become indispensable in various domains, including code generation, reasoning tasks and agent systems. While open-access code LLMs are in…