78 citations · 78 across the 3 of their papers we have counts for
4 papers
The Battery Price of edge AI: A study of the Environmental Impact of LLM Inference on Mobile Devices
Édouard Guégain, Tristan Coignion
The rapid diffusion of generative artificial intelligence raises privacy, latency, and performance concerns that motivate a shift toward "local-first" AI, where inferences are perf…
Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations
Nada Zine, Tristan Coignion, Vincenzo Stoico +4
Large Language Models are reshaping how software is developed and maintained. They are typically deployed in production using inference engines such as vLLM, which can efficiently…
Green My LLM: Studying the key factors affecting the energy consumption of code assistants
Tristan Coignion, Clément Quinton, Romain Rouvoy
In recent years,Large Language Models (LLMs) have significantly improved in generating high-quality code, enabling their integration into developers' Integrated Development Environ…
A Performance Study of LLM-Generated Code on Leetcode
Tristan Coignion, Clément Quinton, Romain Rouvoy
This study evaluates the efficiency of code generation by Large Language Models (LLMs) and measures their performance against human-crafted solutions using a dataset from Leetcode.…