Author

A. Mastropaolo

h-index 16 View on Semantic Scholar

We have 3 of 75 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Jul 2026

Revisiting code readability improvement with LLMs: A critical assessment of fine-tuned models

Assessing whether fine-tuning on available developer readability improvements is actually needed given the recent advances in general-purpose LLMs results in sensibly poorer readability recommendations as compared to LLMs used in a zero-shot setting, with GPT-4.1 being the one achieving the best results.

Antonio Vitale, Emanuela Guglielmi, Valentina Piantadosi et al. · Empirical Software Engineeri... · 0 citations

#large language models Jul 2026

Large Language Models for Code Generation from Multilingual Prompts: A Curated Benchmark and a Study on Code Quality

The results show that English prompts do not consistently produce the best functional correctness or code quality, the impact of prompt language depends on both the programming language and the LLM, and generated code frequently mixes English with the prompt language in comments and string literals.

Saima Afrin, Alessandro Midolo, C. Escobar-Velasquez et al. · arXiv.org · 0 citations

Jul 2026

Quantize with Confidence? An Empirical Study of Quantization for Code Generation

Six state-of-the-art quantization methods are evaluated on two representative large code model families using the multilingual McEval and CoderEval benchmarks for Python and Java to provide practical guidance for selecting quantization strategies for deploying large code models on resource-constrained hardware.

Saima Afrin, MD Zahidul Haque, A. Mastropaolo · arXiv.org · 0 citations