5 papers
Efficient and Scalable Provenance Tracking for LLM-Generated Code Snippets
Andrea Gurioli, Davide D'Ascenzo, Federico Pennino +2
Large language models (LLMs) for code completion and generation are increasingly used in software development, yet they may reproduce training examples verbatim and without authors…
From Reasoning to Code: GRPO Optimization for Underrepresented Languages
Federico Pennino, Bianca Raimondi, Massimo Rondelli +2
Generating accurate and executable code using Large Language Models (LLMs) remains a significant challenge for underrepresented programming languages, such as Prolog and Lisp, due…
Do not copy and paste! Rewriting strategies for code retrieval
Andrea Gurioli, Federico Pennino, Maurizio Gabbrielli
Embedding-based code retrieval often suffers when encoders overfit to surface syntax. Prior work mitigates this by using LLMs to rephrase queries and corpora into a normalized styl…
MoSE: Hierarchical Self-Distillation Enhances Early Layer Embeddings
Andrea Gurioli, Federico Pennino, João Monteiro +1
Deploying language models often requires navigating accuracy vs. performance trade-offs to meet latency constraints while preserving utility. Traditional model distillation reduces…
Is This You, LLM? Recognizing AI-written Programs with Multilingual Code Stylometry
Andrea Gurioli, Maurizio Gabbrielli, Stefano Zacchiroli
With the increasing popularity of LLM-based code completers, like GitHub Copilot, the interest in automatically detecting AI-generated code is also increasing-in particular in cont…