Contributors profile modelization in crowdsourcing platforms. - Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall; Arnaud Martin 001 (CoRR, 2018)

Modeling Uncertainty and Inaccuracy on Data from Crowdsourcing Platforms: MONITOR. - Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall; Arnaud Martin 001 (ICTAI, 2019)

Modélisation de l'incertitude et de l'imprécision de données de crowdsourcing : MONITOR. - Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall; Arnaud Martin 001 (EGC, 2020)

Validation of Smets' Hypothesis in the Crowdsourcing Environment. - Constance Thierry; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (BELIEF, 2021)

Évaluation de la qualité des contributions et des contributeurs sur plateformes de crowdsourcing. (Evaluation of the quality of contributions and contributors on crowdsourcing platforms). - Constance Thierry (2021)

Real Bird Dataset with Imprecise and Uncertain Values. - Constance Thierry; Arthur Hoarau; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (BELIEF, 2022)

Datasets with Rich Labels for Machine Learning. - Arthur Hoarau; Constance Thierry; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (FUZZ, 2023)

Modeling evolutionary responses in crowdsourcing MCQ using belief function theory. - Constance Thierry; Arnaud Martin 001; Yolande Le Gall; Jean-Christophe Dubois (KES, 2023)

Estimation of the qualification and behavior of a contributor and aggregation of his answers in a crowdsourcing context. - Constance Thierry; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (Expert Syst. Appl., 2023)

A Mean Distance Between Elements of Same Class for Rich Labels. - Arthur Hoarau; Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall (BELIEF, 2024)

Automated Hierarchical Conflict Reduction for Crowdsourced Annotation Tasks Using Belief Functions. - Constance Thierry; David Gross-Amblard; Yolande Le Gall; Jean-Christophe Dubois (BELIEF, 2024)

HEADWORK: a Data-centric Crowdsourcing Platform for Complex Tasks and Participants. - David Gross-Amblard; Marion Tommasi; Iandry Rakotoniaina; Constance Thierry; Rituraj Singh; Leo Jacoboni (EDBT, 2024)

Quantifying and Leveraging Uncertain and Imprecise Answers in Multiple Choice Questionnaires for Crowdsourcing: Quantifier et exploiter des réponses incertaines et imprécises dans des questionnaires à choix multiples pour le crowdsourcing. - Constance Thierry; Géry Casiez; Jean-Christophe Dubois; Yolande Le Gall; Sylvain Malacria; Thomas Pietrzak; Arnaud Martin 001; Pierrick Uro (IHM, 2024)

Credal Knowledge Tracing for Imprecise and Uncertain MCQ. - Dorra Sassi; Constance Thierry; David Gross-Amblard (IDA, 2025)

Multi-Dimensional Exploration of Media Collection Metadata. - Omar Shahbaz Khan; Aaron Duane; Hariz Hasnan; Noé Le Blavec; Pierre Ouvrard; Johan Verdon; Laurent d'Orazio; Constance Thierry; Björn Þór Jónsson 001 (MMM (5), 2025)

FPPO: Theory of Belief Functions for more reliable Single and Multi-Agent Systems in Deep Reinforcement Learning. - Amgad A. Mahmoud; Constance Thierry; Frédéric Andrès; Andreas Pester; Nicolas Grenèche; Hesham Ali 001; Shihori Tanabe; Maha Muttardi (Zenodo, 2025)