activity
20172024
most citedAn Evaluation Framework for Attributed Information Retrieval using Large Language Models

4 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2024★ 4 cited

An Evaluation Framework for Attributed Information Retrieval using Large Language Models

Hanane Djeddal, Pierre Erbacher, Raouf Toukal +4

With the growing success of Large Language models (LLMs) in information-seeking scenarios, search engines are now adopting generative approaches to provide answers along with in-li…

cs.CL2021★ 2 cited

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…

cs.IR2021

TSSuBERT: Tweet Stream Summarization Using BERT

Alexis Dusart, Karen Pinel-Sauvagnat, Gilles Hubert

The development of deep neural networks and the emergence of pre-trained language models such as BERT allow to increase performance on many NLP tasks. However, these models do not…

cs.IR2021

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…

cs.IR2017

Everything You Always Wanted to Know About TREC RTS* (*But Were Afraid to Ask)

Gilles Hubert, Jose G. Moreno, Karen Pinel-Sauvagnat +1

The TREC Real-Time Summarization (RTS) track provides a framework for evaluating systems monitoring the Twitter stream and pushing tweets to users according to given profiles. It i…