no code implementations • 11 Apr 2022 • Van Bach Nguyen, Kanishka Ghosh Dastidar, Michael Granitzer, Wissam Siblini
We believe that future works on this new paradigm will have a significant impact on the detection of compromised cards.
no code implementations • ACL 2021 • Wissam Siblini, Baris Sayil, Yacine Kessaci
With the explosion of chatbot applications, Conversational Question Answering (CQA) has generated a lot of interest in recent years.
no code implementations • 20 Jul 2021 • Wissam Siblini, Guillaume Coter, Rémy Fabry, Liyun He-Guelton, Frédéric Oblé, Bertrand Lebichot, Yann-Aël Le Borgne, Gianluca Bontempi
The dark face of digital commerce generalization is the increase of fraud attempts.
1 code implementation • 16 Oct 2020 • Wissam Siblini, Mohamed Challal, Charlotte Pasqual
Open Domain Question Answering (ODQA) on a large-scale corpus of documents (e. g. Wikipedia) is a key challenge in computer science.
no code implementations • 10 Oct 2019 • Wissam Siblini, Charlotte Pasqual, Axel Lavielle, Mohamed Challal, Cyril Cauchois
Moreover, using a recently published large eQA French dataset, we are able to further show that (1) zero-shot transfer provides results really close to a direct training on the target language and (2) combination of transfer and training on target is the best option overall.
1 code implementation • 6 Sep 2019 • Wissam Siblini, Jordan Fréry, Liyun He-Guelton, Frédéric Oblé, Yi-Qing Wang
Machine learning models deployed in real-world applications are often evaluated with precision-based metrics such as F1-score or AUC-PR (Area Under the Curve of Precision Recall).
no code implementations • ICML 2018 • Wissam Siblini, Pascale Kuntz, Frank Meyer
Extreme Multi-label Learning (XML) considers large sets of items described by a number of labels that can exceed one million.