collaborators

6 papers

cs.AI2026

Beyond Accuracy: Measuring Logical Compliance of Predictive Models

Guillaume Olivier Delplanque, Pierre Genevès, Nabil Layaïda +1

Machine learning models are predominantly evaluated through predictive performance metrics such as ranking quality, prediction error, or classification accuracy. While these metric…

cs.PL2026

Towards Multiparty Session Types for Highly-Concurrent and Fault-Tolerant Web Applications

Richard Casetta, Nils Gesbert, Pierre Genevès

Modern web applications combine persistent state updates, concurrent interactions, and unreliable communication with external services. Failures such as timeouts can occur after pa…

cs.DB2026

Optimizing Relational Queries over Array-Valued Data in Columnar Systems

Maroua Zeblah, Etienne Couritas, Sarah Chlyah +3

Modern analytical workloads increasingly combine relational data with array-valued attributes. While columnar database systems efficiently process such workloads, their ability to…

cs.DB2025

Distributed Evaluation of Graph Queries using Recursive Relational Algebra

Sarah Chlyah, Pierre Genevès, Nabil Layaïda

We present a system called Dist--RA for the distributed evaluation of recursive graph queries. Dist--RA builds on the recursive relational algebra and extends it with evalu…

cs.DB2025

Schema-Based Query Optimisation for Graph Databases

Chandan Sharma, Pierre Genevès, Nils Gesbert +1

Recursive graph queries are increasingly popular for extracting information from interconnected data found in various domains such as social networks, life sciences, and business a…

cs.AI2025

On Scaling Neurosymbolic Programming through Guided Logical Inference

Thomas Jean-Michel Valentin, Luisa Sophie Werner, Pierre Genevès +1

Probabilistic neurosymbolic learning seeks to integrate neural networks with symbolic programming. Many state-of-the-art systems rely on a reduction to the Probabilistic Weighted M…