Vincent Grari

According to our database, Vincent Grari authored at least 19 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Agentic Adversarial QA for Improving Domain-Specific LLMs.

Vincent Grari, Ciprian Tomoiaga, Sylvain Lamprier, Tatsunori Hashimoto, Marcin Detyniecki

CoRR, February, 2026

2025

Energy Scaling Laws for Diffusion Models: Quantifying Compute and Carbon Emissions in Image Generation.

Aniketh Iyengar, Jiaqi Han, Boris Ruf, Vincent Grari, Marcin Detyniecki, Stefano Ermon

CoRR, November, 2025

ACT: Agentic Classification Tree.

Vincent Grari, Tim Arni, Thibault Laugel, Sylvain Lamprier, James Zou, Marcin Detyniecki

CoRR, September, 2025

Controlled Model Debiasing through Minimal and Interpretable Updates.

Federico Di Gennaro, Thibault Laugel, Vincent Grari, Marcin Detyniecki

Trans. Mach. Learn. Res., 2025

When Mitigating Bias is Unfair: Multiplicity and Arbitrariness in Algorithmic Group Fairness.

Natasa Krco, Thibault Laugel, Vincent Grari, Jean-Michel Loubes, Marcin Detyniecki

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2025

SAKE: Steering Activations for Knowledge Editing.

Marco Scialanga, Thibault Laugel, Vincent Grari, Marcin Detyniecki

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Post-processing fairness with minimal changes.

Federico Di Gennaro, Thibault Laugel, Vincent Grari, Xavier Renard, Marcin Detyniecki

CoRR, 2024

OptiGrad: A Fair and more Efficient Price Elasticity Optimization via a Gradient Based Learning.

Vincent Grari, Marcin Detyniecki

CoRR, 2024

On the Fairness ROAD: Robust Optimization for Adversarial Debiasing.

Vincent Grari, Thibault Laugel, Tatsunori Hashimoto, Sylvain Lamprier, Marcin Detyniecki

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Adversarial learning for counterfactual fairness.

Vincent Grari, Sylvain Lamprier, Marcin Detyniecki

Mach. Learn., March, 2023

2022

Adversarial mitigation to reduce unwanted biases in machine learning. (Réduire les biais indésirables en apprentissage automatique par atténuation adverse).

Vincent Grari

PhD thesis, 2022

A fair pricing model via adversarial learning.

Vincent Grari, Arthur Charpentier, Sylvain Lamprier, Marcin Detyniecki

CoRR, 2022

Fairness without the Sensitive Attribute via Causal Variational Autoencoder.

Vincent Grari, Sylvain Lamprier, Marcin Detyniecki

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Learning Unbiased Representations via Rényi Minimization.

Vincent Grari, Oualid El Hajouji, Sylvain Lamprier, Marcin Detyniecki

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Enforcing Individual Fairness via Rényi Variational Inference.

Vincent Grari, Oualid El Hajouji, Sylvain Lamprier, Marcin Detyniecki

Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

Achieving Fairness with Decision Trees: An Adversarial Approach.

Vincent Grari, Boris Ruf, Sylvain Lamprier, Marcin Detyniecki

Data Sci. Eng., 2020

Fairness-Aware Neural Rényi Minimization for Continuous Features.

Vincent Grari, Sylvain Lamprier, Marcin Detyniecki

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Fairness-Aware Neural Réyni Minimization for Continuous Features.

Vincent Grari, Boris Ruf, Sylvain Lamprier, Marcin Detyniecki

CoRR, 2019

Fair Adversarial Gradient Tree Boosting.

Vincent Grari, Boris Ruf, Sylvain Lamprier, Marcin Detyniecki

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019