activity
20242026
most citedSafeguarding Deliberation in Digital Democracy

1 citations · 1 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Characterizing Necessary Losers to Explain Tournaments Solutions

Contet Clément, Umberto Grandi, Jérôme Mengin

We study the problem of formally explaining why a candidate was not selected by a given tournament rule, by identifying sub-tournaments in which the candidate loses independently o…

cs.AI2026

Efficient Elicitation of Collective Disagreements

Mohamed Ouaguenouni, Felipe Garrido-Lucero, Umberto Grandi +2

We analyze the structure of the disagreement among a population of voters over a set of alternatives. Surveys typically ask either for pairwise comparisons, simple and intuitive fo…

cs.GT2026

Prophet Inequalities with Delayed and Uncertain Acceptance

Emile Martinez, Felipe Garrido-Lucero, Umberto Grandi +1

We introduce the *prophet inequality with delayed and uncertain acceptance* model, a variant of the classical prophet inequality in which a decision-maker sequentially evaluates op…

cs.GT2025

Stability in Online Assignment Games

Emile Martinez, Felipe Garrido-Lucero, Umberto Grandi

The assignment game models a housing market where buyers and sellers are matched, and transaction prices are set so that the resulting allocation is stable. Shapley and Shubik show…

cs.AI2025

Explaining Tournament Solutions with Minimal Supports

Clément Contet, Umberto Grandi, Jérôme Mengin

Tournaments are widely used models to represent pairwise dominance between candidates, alternatives, or teams. We study the problem of providing certified explanations for why a ca…

cs.CY2025

Algorithmic Shortlisting in Participatory Budgeting

Juan Zambrano, Juan Ignacio Zambrano, Clément Contet +5

Participatory budgeting is a democratic innovation that allows citizens to propose and vote on public investment projects. To help organizers manage large volumes of submissions, w…

cs.CY2025★ 1 cited

Safeguarding Deliberation in Digital Democracy

Jairo Gudiño-Rosero, Clément Contet, Juan Ignacio Zambrano +2

Large Language Models (LLMs) are gaining traction in digital democracy experiments as a method to aggregate preferences through deliberation and express the resulting common ground…

cs.AI2024

Abductive and Contrastive Explanations for Scoring Rules in Voting

Clément Contet, Umberto Grandi, Jérôme Mengin

We view voting rules as classifiers that assign a winner (a class) to a profile of voters' preferences (an instance). We propose to apply techniques from formal explainability, mos…