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cs.SE2026
Unraveling the Efficacy of Neuron Coverage Criteria on Testing Large Language Models
Xiaoning Ren, Jiayang Song, Chongyang Liu +3
Neuron coverage criteria aim to assess test suite quality and guide test input generation, but their effectiveness for Transformer-based language models remains unclear. We evaluat…
cs.SE2025
Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning
Xiaoning Ren, Qiang Hu, Wei Ma +6
Large language models (LLMs) have recently shown impressive results on diverse code-related tasks, benefiting from large-scale training and instruction tuning. However, studies rev…