activity
20002026
most citedSimulating Non Stationary Operators in Search Algorithms

11 citations · 15 across the 10 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Position Spaces and Graphs

Rita-Nathalia Assaf, Tom Davot, Frédéric Lardeux +1

In this paper, we introduce position graphs, a graph-based reasoning framework based on the formalization of position spaces. This framework utilizes two strict partial orders, rep…

cs.AI2026

Stein Variational Black-Box Combinatorial Optimization

Thomas Landais, Olivier Goudet, Adrien Goëffon +2

Combinatorial black-box optimization in high-dimensional settings demands a careful trade-off between exploiting promising regions of the search space and preserving sufficient exp…

cs.CL2025

Progress Ratio Embeddings: An Impatience Signal for Robust Length Control in Neural Text Generation

Ivanhoé Botcazou, Tassadit Amghar, Sylvain Lamprier +1

Modern neural language models achieve high accuracy in text generation, yet precise control over generation length remains underdeveloped. In this paper, we first investigate a rec…

cs.LG2025

Black-Box Combinatorial Optimization with Order-Invariant Reinforcement Learning

Olivier Goudet, Quentin Suire, Adrien Goëffon +2

We introduce an order-invariant reinforcement learning framework for black-box combinatorial optimization. Classical estimation-of-distribution algorithms (EDAs) often rely on lear…

cs.NE2025

Discovering new robust local search algorithms with neuro-evolution

Mohamed Salim Amri Sakhri, Adrien Goëffon, Olivier Goudet +2

This paper explores a novel approach aimed at overcoming existing challenges in the realm of local search algorithms. Our aim is to improve the decision process that takes place wi…

cs.IR2022★ 1 cited

A two-stage approach for table extraction in invoices

Thomas Saout, Frédéric Lardeux, Frédéric Saubion

The automated analysis of administrative documents is an important field in document recognition that is studied for decades. Invoices are key documents among these huge amounts of…