Théo Matricon

According to our database, Théo Matricon authored at least 15 papers between 2021 and 2026.

Collaborative distances:

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

2026

Promises, Perils, and (Timely) Heuristics for Mining Coding Agent Activity.

Romain Robbes, Théo Matricon, Thomas Degueule, André C. Hora, Stefano Zacchiroli

CoRR, January, 2026

Agentic Much? Adoption of Coding Agents on GitHub.

Romain Robbes, Théo Matricon, Thomas Degueule, André C. Hora, Stefano Zacchiroli

CoRR, January, 2026

LTL_f Learning Meets Boolean Set Cover.

Gabriel Bathie, Nathanaël Fijalkow, Théo Matricon, Baptiste Mouillon, Pierre Vandenhove

Proceedings of the Tools and Algorithms for the Construction and Analysis of Systems, 2026

2025

Efficiently Ranking Software Variants with Minimal Benchmarks.

Théo Matricon, Mathieu Acher, Helge Spieker, Arnaud Gotlieb

CoRR, September, 2025

Re-evaluating metamorphic testing of chess engines: A replication study.

Axel Martin, Djamel Eddine Khelladi, Théo Matricon, Mathieu Acher

Inf. Softw. Technol., 2025

Prompting for Performance: Exploring LLMs for Configuring Software.

Helge Spieker, Théo Matricon, Nassim Belmecheri, Jørn Eirik Betten, Gauthier Le Bartz Lyan, Heraldo Borges, Quentin Mazouni, Dennis Gross, Arnaud Gotlieb, Mathieu Acher

Proceedings of the 37th IEEE International Conference on Tools with Artificial Intelligence, 2025

Eco Search: A No-delay Best-First Search Algorithm for Program Synthesis.

Théo Matricon, Nathanaël Fijalkow, Guillaume Lagarde

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Domain agnostic techniques for scaling up program synthesis. (Techniques agnostiques au domaine pour l'accélération de la synthèse de programmes).

Théo Matricon

PhD thesis, 2024

EcoSearch: A Constant-Delay Best-First Search Algorithm for Program Synthesis.

Théo Matricon, Nathanaël Fijalkow, Guillaume Lagarde

CoRR, 2024

Theoretical foundations for programmatic reinforcement learning.

Guruprerana Shabadi, Nathanaël Fijalkow, Théo Matricon

CoRR, 2024

2023

WikiCoder: Learning to Write Knowledge-Powered Code.

Théo Matricon, Nathanaël Fijalkow, Gaëtan Margueritte

Proceedings of the Model Checking Software - 29th International Symposium, 2023

2022

DeepSynth: Scaling Neural Program Synthesis with Distribution-based Search.

Théo Matricon, Nathanaël Fijalkow, Guillaume Lagarde, Kevin Ellis

J. Open Source Softw., October, 2022

Challenges of Acquiring Compositional Inductive Biases via Meta-Learning.

Marie Anastacio, Théo Matricon, Holger H. Hoos

Proceedings of the ECML/PKDD Workshop on Meta-Knowledge Transfer, 2022

Scaling Neural Program Synthesis with Distribution-Based Search.

Nathanaël Fijalkow, Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh Nayan Potta

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Statistical Comparison of Algorithm Performance Through Instance Selection.

Théo Matricon, Marie Anastacio, Nathanaël Fijalkow, Laurent Simon, Holger H. Hoos

Proceedings of the 27th International Conference on Principles and Practice of Constraint Programming, 2021