From the 2 of 22 linked papers with an AI index.
22 papers
Pattern over Pixels: Measuring Pattern Completion Bias in Multimodal Code Generation
Khai-Nguyen Nguyen, Oscar Chaparro, Antonio Mastropaolo
Multimodal large language models (MLLMs) are increasingly used to translate webpage screenshots into front-end code, but repeated UI patterns may sway them toward visually incorrec…
Large Language Models for Code Generation from Multilingual Prompts: A Curated Benchmark and a Study on Code Quality
Saima Afrin, Alessandro Midolo, Camilo Escobar-Velásquez +5
The paper introduces a curated multilingual benchmark to study how the natural language of prompts influences code generation quality of large language models, evaluating functiona…
Quantize with Confidence? An Empirical Study of Quantization for Code Generation
Saima Afrin, Md. Zahidul Haque, Antonio Mastropaolo
The paper empirically evaluates six post‑training quantization methods for large code generation models, measuring their effects on functional correctness, code quality, and robust…
Prior Bias in Vision Language Models on UML Diagram Interpretation
Zaiyu Cheng, Khai-Nguyen Nguyen, Antonio Mastropaolo
Vision Language Models (VLMs) are increasingly applied to software engineering artifacts, especially UML class diagrams whose meaning depends on visual notation. Yet, it is unclear…
Parameter-Efficient Multi-Task Fine-Tuning in Code-Related Tasks
Md Zahidul Haque, Saima Afrin, Antonio Mastropaolo
Large Language Models (LLMs) have proven highly effective in automating software engineering tasks, bridging natural language and code semantics to achieve notable results in code…
Rethinking Software Empirical Studies with Structural Causal Models
Daniel Rodriguez-Cardenas, Aya Garryyeva, David Nader Palacio +2
Causal Inference offers a fundamental approach for advancing empirical software engineering (ESE) beyond traditional statistical association, enabling researchers to rigorously ide…