38 citations · 93 across the 19 of their papers we have counts for
5 papers · 1 filter
Does Structure Matter? Leveraging Data-to-Text Generation for Answering Complex Information Needs
Hanane Djeddal, Thomas Gerald, Laure Soulier +2
In this work, our aim is to provide a structured answer in natural language to a complex information need. Particularly, we envision using generative models from the perspective of…
Learning a subspace of policies for online adaptation in Reinforcement Learning
Jean-Baptiste Gaya, Laure Soulier, Ludovic Denoyer
Deep Reinforcement Learning (RL) is mainly studied in a setting where the training and the testing environments are similar. But in many practical applications, these environments…
Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation
Clément Rebuffel, Thomas Scialom, Laure Soulier +5
QuestEval is a reference-less metric used in text-to-text tasks, that compares the generated summaries directly to the source text, by automatically asking and answering questions.…
Controlling Hallucinations at Word Level in Data-to-Text Generation
Clément Rebuffel, Marco Roberti, Laure Soulier +3
Data-to-Text Generation (DTG) is a subfield of Natural Language Generation aiming at transcribing structured data in natural language descriptions. The field has been recently boos…
Studying Catastrophic Forgetting in Neural Ranking Models
Jesus Lovon-Melgarejo, Laure Soulier, Karen Pinel-Sauvagnat +1
Several deep neural ranking models have been proposed in the recent IR literature. While their transferability to one target domain held by a dataset has been widely addressed usin…