13 citations · 29 across the 4 of their papers we have counts for
6 papers
Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection
Maxime Labonne, Sean Moran
This paper investigates the effectiveness of large language models (LLMs) in email spam detection by comparing prominent models from three distinct families: BERT-like, Sentence Tr…
Estimating class separability of text embeddings with persistent homology
Kostis Gourgoulias, Najah Ghalyan, Maxime Labonne +3
This paper introduces an unsupervised method to estimate the class separability of text datasets from a topological point of view. Using persistent homology, we demonstrate how tra…
Predicting Bandwidth Utilization on Network Links Using Machine Learning
Maxime Labonne, Charalampos Chatzinakis, Alexis Olivereau
Predicting the bandwidth utilization on network links can be extremely useful for detecting congestion in order to correct them before they occur. In this paper, we present a solut…
Toward Formal Data Set Verification for Building Effective Machine Learning Models
Jorge López, Maxime Labonne, Claude Poletti
In order to properly train a machine learning model, data must be properly collected. To guarantee a proper data collection, verifying that the collected data set holds certain pro…
Short-Term Flow-Based Bandwidth Forecasting using Machine Learning
Maxime Labonne, Jorge López, Claude Poletti +1
This paper proposes a novel framework to predict traffic flows' bandwidth ahead of time. Modern network management systems share a common issue: the network situation evolves betwe…
Priority Flow Admission and Routing in SDN: Exact and Heuristic Approaches
Jorge López, Maxime Labonne, Claude Poletti +1
This paper proposes a novel admission and routing scheme which takes into account arbitrarily assigned priorities for network flows. The presented approach leverages the centralize…