A heuristic optimization of Bayesian incentive-compatible cake-cutting. - Lê Nguyên Hoang; François Soumis; Georges Zaccour (Comput. Oper. Res., 2016)

Strategy-proofness of the randomized Condorcet voting system. - Lê Nguyên Hoang (Soc. Choice Welf., 2017)

Deep Learning Works in Practice. But Does it Work in Theory? - Lê Nguyên Hoang; Rachid Guerraoui (CoRR, 2018)

A Roadmap for the Value-Loading Problem. - Lê Nguyên Hoang (CoRR, 2018)

Towards Robust End-to-End Alignment. - Lê Nguyên Hoang (SafeAI@AAAI, 2019)

The return function: A new computable perspective on Bayesian-Nash equilibria. - Lê Nguyên Hoang; François Soumis; Georges Zaccour (Eur. J. Oper. Res., 2019)

Collaborative Learning as an Agreement Problem. - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Arsany Guirguis; Lê Nguyên Hoang; Sébastien Rouault (CoRR, 2020)

Purely Bayesian counterfactuals versus Newcomb's paradox. - Lê Nguyên Hoang (CoRR, 2020)

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning). - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Arsany Guirguis; Lê-Nguyên Hoang; Sébastien Rouault (NeurIPS, 2021)

Strategyproof Learning: Building Trustworthy User-Generated Datasets. - Sadegh Farhadkhani; Rachid Guerraoui; Lê-Nguyên Hoang (CoRR, 2021)

Tournesol: A quest for a large, secure and trustworthy database of reliable human judgments. - Lê-Nguyên Hoang; Louis Faucon; Aidan Jungo; Sergei Volodin; Dalia Papuc; Orfeas Liossatos; Ben Crulis; Mariame Tighanimine; Isabela Constantin; Anastasiia Kucherenko; Alexandre Maurer; Felix Grimberg; et al. (CoRR, 2021)

An Equivalence Between Data Poisoning and Byzantine Gradient Attacks. - Sadegh Farhadkhani; Rachid Guerraoui; Lê Nguyên Hoang; Oscar Villemaud (ICML, 2022)

Making Byzantine Decentralized Learning Efficient. - Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Lê Nguyên Hoang; Rafael Pinot; John Stephan (CoRR, 2022)

On the Impossible Safety of Large AI Models. - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Lê-Nguyên Hoang; Rafael Pinot; John Stephan (CoRR, 2022)

Tournesol: Permissionless Collaborative Algorithmic Governance with Security Guarantees. - Romain Beylerian; Bérangère Colbois; Louis Faucon; Lê Nguyên Hoang; Aidan Jungo; Alain Le Noac'h; Adrien Matissart (CoRR, 2022)

Genuinely distributed Byzantine machine learning. - El-Mahdi El-Mhamdi; Rachid Guerraoui; Arsany Guirguis; Lê-Nguyên Hoang; Sébastien Rouault (Distributed Comput., 2022)

Removing algorithmic discrimination (with minimal individual error). - El-Mahdi El-Mhamdi; Rachid Guerraoui; Lê-Nguyên Hoang; Alexandre Maurer (Theor. Comput. Sci., 2022)

On the Strategyproofness of the Geometric Median. - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Lê-Nguyên Hoang (AISTATS, 2023)

Robust Collaborative Learning with Linear Gradient Overhead. - Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Lê-Nguyên Hoang; Rafael Pinot; John Stephan (ICML, 2023)

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons. - Julien Fageot; Sadegh Farhadkhani; Lê-Nguyên Hoang; Oscar Villemaud (AAAI, 2024)

Robust Sparse Voting. - Youssef Allouah; Rachid Guerraoui; Lê-Nguyên Hoang; Oscar Villemaud (AISTATS, 2024)

The poison of dimensionality. - Lê-Nguyên Hoang (CoRR, 2024)

On Goodhart's law, with an application to value alignment. - El-Mahdi El-Mhamdi; Lê-Nguyên Hoang (CoRR, 2024)

Should YouTube make recommendations for the climate? - Martin Gibert; Lê-Nguyên Hoang; Maxime Lambrecht (Ethics Inf. Technol., 2024)

A case for specialisation in non-human entities. - El-Mahdi El-Mhamdi; Lê-Nguyên Hoang; Mariame Tighanimine (CoRR, 2025)

Generalizing while preserving monotonicity in comparison-based preference learning models. - Julien Fageot; Peva Blanchard; Gilles Bareilles; Lê-Nguyên Hoang (CoRR, 2025)

On Monotonicity in AI Alignment. - Gilles Bareilles; Julien Fageot; Lê-Nguyên Hoang; Peva Blanchard; Wassim Bouaziz; Sébastien Rouault; El-Mahdi El-Mhamdi (CoRR, 2025)