3 papers
cs.SE2026
Can Large Language Models Implement Agent-Based Models? An ODD-based Replication Study
Nuno Fachada, Daniel Fernandes, Carlos M. Fernandes +1
Large language models (LLMs) can now synthesize non-trivial executable code from textual descriptions, raising an important question: can LLMs reliably implement agent-based models…
cs.SE2025
GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries
Nuno Fachada, Daniel Fernandes, Carlos M. Fernandes +2
Large Language Models (LLMs) have advanced rapidly as tools for automating code generation in scientific research, yet their ability to interpret and use unfamiliar Python APIs for…
cs.SE2025
DeepSeek-V3, GPT-4, Phi-4, and LLaMA-3.3 generate correct code for LoRaWAN-related engineering tasks
Daniel Fernandes, João P. Matos-Carvalho, Carlos M. Fernandes +1
This paper investigates the performance of 16 Large Language Models (LLMs) in automating LoRaWAN-related engineering tasks involving optimal placement of drones and received power…