22 citations · 29 across the 5 of their papers we have counts for
5 papers
Towards Better Code Understanding in Decoder-Only Models with Contrastive Learning
Jiayi Lin, Yanlin Wang, Yibiao Yang +2
Recent advances in large-scale code generation models have led to remarkable progress in producing high-quality code. These models are trained in a self-supervised manner on extens…
Scaling Laws Behind Code Understanding Model
Jiayi Lin, Hande Dong, Yutao Xie +1
The scaling law is becoming a fundamental law in many machine learning areas. That is, test error falls off with the power law when increasing training data, model size, and comput…
AcademicGPT: Empowering Academic Research
Shufa Wei, Xiaolong Xu, Xianbiao Qi +21
Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Yet, many of these advanced LLMs are tailored for broad, g…
Bridging Code Semantic and LLMs: Semantic Chain-of-Thought Prompting for Code Generation
Yingwei Ma, Yue Yu, Shanshan Li +5
Large language models (LLMs) have showcased remarkable prowess in code generation. However, automated code generation is still challenging since it requires a high-level semantic m…
Survey of Code Search Based on Deep Learning
Yutao Xie, Jiayi Lin, Hande Dong +2
Code writing is repetitive and predictable, inspiring us to develop various code intelligence techniques. This survey focuses on code search, that is, to retrieve code that matches…