I am a postdoctoral researcher in the Distributed Information Systems Laboratory at the Swiss Federal Institute of Technology Lausanne (EPFL).
Prior to joining EPFL, I spent 3 years as a Ph.D. researcher in the Department of Computer Science, Data and Artificial Intelligence at the Polytechnic Institute of Paris (IP Paris), funded by a Google doctoral fellowship and working on deep learning models for natural language processing. I was supervised by Prof. Thomas Bonald (Télécom Paris) and Dr. Lucas Dixon (Google). My thesis focus was on the analysis and control of online interactions through Neural Natural Language Processing.
I hold an engineering degree in Electrical Engineering and Computer Science from CentraleSupelec and a M.Eng. in Data Science & Systems from the University of California, Berkeley. Before my PhD, I worked as a research engineer at A*STAR Institute for Infocomm Research (I²R).
My research aims at leveraging the capabilities of Large Language Models to address issues emerging from online discussions. Web interactions on social media and news platforms may have serious consequences in real life but I am convinced that Artificial Intelligence technologies are poised to foster more constructive online behaviors. More generally, I am interested in applications of machine learning and I am always curious in learning new topics in computer science and engineering.
SAGESSE: A System for Argument Generation, Extraction and Structuring of Social Exchanges.
Nicolas Almerge*, Matteo Santelmo*, Ilker Gül*, Amin Asadi Sarijalou*, Rémi Lebret†,
Leo Laugier†, Karl Aberer
WSDM 2025 Demonstration
[ PDF | Demo | Poster]
CRAB: Assessing the Strength of Causal Relationships Between Real-world Events.
Angelika Romanou, Syrielle Montariol, Debjit Paul, Leo Laugier, Karl Aberer, Antoine Bosselut
EMNLP 2023
[ PDF]
JUAGE at SemEval-2023 Task 10: Parameter Efficient Classification.
Jeffrey Sorensen, Katerina Korre, John Pavlopoulos, Katrin Tomanek, Nithum Thain, Lucas Dixon, Leo Laugier
SemEval 2023
[ PDF]
Harmful Language Datasets: An Assessment of Robustness.
Katerina Korre, John Pavlopoulos, Jeffrey Sorensen, Leo Laugier, Ion Androutsopoulos, Lucas Dixon, Alberto Barrón-cedeño
ACL 2023 Workshop on Online Abuse and Harms
[ PDF]
KNNs of Semantic Encodings for Rating Prediction.
Leo Laugier, Raghuram Vadapalli, Thomas Bonald, Lucas Dixon
IEEE CIC 2023
[ PDF]
Toxicity Detection can be Sensitive to the Conversational Context.
Alexandros Xenos, John Pavlopoulos, Ion Androutsopoulos, Lucas Dixon, Jeffrey Sorensen, Leo Laugier
First Monday, 27(5) (September 2022)
[ HTML]
From the Detection of Toxic Spans in Online Discussions to the Analysis of Toxic-to-Civil Transfer.
John Pavlopoulos, Leo Laugier, Alexandros Xenos, Jeffrey Sorensen, Ion Androutsopoulos
ACL 2022
[ PDF | Poster | Slides]
Semeval-2021 task 5: Toxic spans detection.
John Pavlopoulos, Jeffrey Sorensen, Leo Laugier, Ion Androutsopoulos
SemEval-2021
[ PDF]
Civil rephrases of toxic texts with self-supervised transformers.
Leo Laugier, John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon
EACL 2021
[ PDF | Poster | Slides]
Encoding Knowledge Graph with Graph CNN for Question Answering.
Leo Laugier*, Anran Wang*, Chuan-Sheng Foo, Theo Guenais, Vijay Chandrasekhar
Representation Learning on Graphs and Manifolds ICLR 2019 Workshop
[ PDF]
Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials.
Leo Laugier, Daniil Bash, Jose Recatala, Hong Kuan Ng, Savitha Ramasamy, Chuan-Sheng Foo, Vijay R. Chandrasekhar, Kedar Hippalgaonkar
Machine Learning for Molecules and Materials NeurIPS 2018 Workshop
[ PDF]
Lina Berrayana (Semester project, Fall 2024): Automated Mediation with Large Language Models (now at IBM Research)
Aybars Yazıcı (Master’s thesis, Fall 2024): Peace Mediator Assistant: An AI tool for analysis of political events
Adriana Orellana (Intern, Summer 2024): Peace Mediator Assistant (now at DemoSquare)
Thibaut de Saivre (Intern, Spring-Summer 2024): Deliberate-Lab and LLM Mediators
Eloi Eynard (Semester project, Fall 2023): Harnessing Large Language Models to De-escalate Online Polarisation (now at NEUR.ON)
Yifei Song (Semester project, Spring 2023): Few-shot learning with parameter-efficient tuning (now at INRIA)