18 citations · 42 across the 6 of their papers we have counts for
8 papers
ORDER: Task-Conditioned Routing for Retrieval-Augmented Generation
Aurélien Pellet, Julien Perez, Marie Puren
Retrieval-Augmented Generation (RAG) pipelines typically rely on a fixed indexing and retrieval configuration determined at preprocessing time. This one-size-fits-all design is ill…
HistoriQA-ThirdRepublic: Multi-Hop Question Answering Corpus for Historical Research, Parliamentary Debates from the French Third Republic (1870-1940)
Aurélien Pellet, Julien Perez, Marie Puren
We present HistoriQA-ThirdRepublic: a French-language dataset of multi-hop historical questions derived from parliamentary debates and newspapers of the French Third Republic. Desi…
Learning Visual Representations with Caption Annotations
Mert Bulent Sariyildiz, Julien Perez, Diane Larlus
Pretraining general-purpose visual features has become a crucial part of tackling many computer vision tasks. While one can learn such features on the extensively-annotated ImageNe…
ReviewQA: a relational aspect-based opinion reading dataset
Quentin Grail, Julien Perez
Deep reading models for question-answering have demonstrated promising performance over the last couple of years. However current systems tend to learn how to cleverly extract a sp…
Non-Markovian Control with Gated End-to-End Memory Policy Networks
Julien Perez, Tomi Silander
Partially observable environments present an important open challenge in the domain of sequential control learning with delayed rewards. Despite numerous attempts during the two la…
Spectral decomposition method of dialog state tracking via collective matrix factorization
Julien Perez
The task of dialog management is commonly decomposed into two sequential subtasks: dialog state tracking and dialog policy learning. In an end-to-end dialog system, the aim of dial…
Dialog state tracking, a machine reading approach using Memory Network
Julien Perez, Fei Liu
In an end-to-end dialog system, the aim of dialog state tracking is to accurately estimate a compact representation of the current dialog status from a sequence of noisy observatio…
Online Learning to Sample
Guillaume Bouchard, Théo Trouillon, Julien Perez +1
Stochastic Gradient Descent (SGD) is one of the most widely used techniques for online optimization in machine learning. In this work, we accelerate SGD by adaptively learning how…