2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CL2023★ 2 cited
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…
cs.SE2023★ 1 cited
One Adapter for All Programming Languages? Adapter Tuning for Code Search and Summarization
Deze Wang, Boxing Chen, Shanshan Li +4
As pre-trained models automate many code intelligence tasks, a widely used paradigm is to fine-tune a model on the task dataset for each programming language. A recent study report…