7 citations · 19 across the 9 of their papers we have counts for
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cs.SE2025★ 1 cited
Clarifying Semantics of In-Context Examples for Unit Test Generation
Chen Yang, Lin Yang, Ziqi Wang +3
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context exa…
cs.SE2025★ 1 cited
A Survey of Reinforcement Learning for Software Engineering
Dong Wang, Hanmo You, Lingwei Zhu +6
Reinforcement Learning (RL) has emerged as a powerful paradigm for sequential decision-making and has attracted growing interest across various domains, particularly following the…
cs.SE2025★ 2 cited
Reflective Unit Test Generation for Precise Type Error Detection with Large Language Models
Chen Yang, Ziqi Wang, Yanjie Jiang +4
Type errors in Python often lead to runtime failures, posing significant challenges to software reliability and developer productivity. Existing static analysis tools aim to detect…