26 citations · 59 across the 24 of their papers we have counts for
4 papers · 1 filter
PACE: Improving Prompt with Actor-Critic Editing for Large Language Model
Yihong Dong, Kangcheng Luo, Xue Jiang +2
Large language models (LLMs) have showcased remarkable potential across various tasks by conditioning on prompts. However, the quality of different human-written prompts leads to s…
Self-collaboration Code Generation via ChatGPT
Yihong Dong, Xue Jiang, Zhi Jin +1
Although Large Language Models (LLMs) have demonstrated remarkable code-generation ability, they still struggle with complex tasks. In real-world software development, humans usual…
Self-planning Code Generation with Large Language Models
Xue Jiang, Yihong Dong, Lecheng Wang +5
Although large language models (LLMs) have demonstrated impressive ability in code generation, they are still struggling to address the complicated intent provided by humans. It is…
CodeScore: Evaluating Code Generation by Learning Code Execution
Yihong Dong, Jiazheng Ding, Xue Jiang +3
A proper code evaluation metric (CEM) profoundly impacts the evolution of code generation, which is an important research field in NLP and software engineering. Prevailing match-ba…