54 citations · 61 across the 5 of their papers we have counts for
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cs.SE2025★ 1 cited
A Systematic Literature Review of Code Hallucinations in LLMs: Characterization, Mitigation Methods, Challenges, and Future Directions for Reliable AI
Cuiyun Gao, Guodong Fan, Chun Yong Chong +5
Model hallucination is one of the most critical challenges faced by Large Language Models (LLMs), especially in high-stakes code intelligence tasks. As LLMs become increasingly int…
cs.LG2025
Efficient Federated Learning with Encrypted Data Sharing for Data-Heterogeneous Edge Devices
Hangyu Li, Hongyue Wu, Guodong Fan +3
As privacy protection gains increasing importance, more models are being trained on edge devices and subsequently merged into the central server through Federated Learning (FL). Ho…
cs.SE2025★ 54 cited
Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering
Ruiqi Wang, Jiyu Guo, Cuiyun Gao +3
Recently, large language models (LLMs) have been deployed to tackle various software engineering (SE) tasks like code generation, significantly advancing the automation of SE tasks…