no code implementations • ACL 2022 • Moussa Kamal Eddine, Guokan Shang, Antoine Tixier, Michalis Vazirgiannis
While traditional natural language generation metrics are fast, they are not very reliable.
1 code implementation • 8 Dec 2023 • Virgile Rennard, Guokan Shang, Damien Grari, Julie Hunter, Michalis Vazirgiannis
In this paper, we present a dataset of French political debates for the purpose of enhancing resources for multi-lingual dialogue summarization.
no code implementations • 28 Nov 2023 • Julie Hunter, Jérôme Louradour, Virgile Rennard, Ismaïl Harrando, Guokan Shang, Jean-Pierre Lorré
We present the Claire French Dialogue Dataset (CFDD), a resource created by members of LINAGORA Labs in the context of the OpenLLM France initiative.
no code implementations • 20 Nov 2023 • Yanzhu Guo, Guokan Shang, Virgile Rennard, Michalis Vazirgiannis, Chloé Clavel
With the increasing amount of problematic peer reviews in top AI conferences, the community is urgently in need of automatic quality control measures.
no code implementations • 16 Nov 2023 • Yanzhu Guo, Guokan Shang, Michalis Vazirgiannis, Chloé Clavel
This study investigates the consequences of training language models on synthetic data generated by their predecessors, an increasingly prevalent practice given the prominence of powerful generative models.
no code implementations • 12 Oct 2022 • Moussa Kamal Eddine, Guokan Shang, Michalis Vazirgiannis
The rapid development of large pretrained language models has revolutionized not only the field of Natural Language Generation (NLG) but also its evaluation.
2 code implementations • 8 Aug 2022 • Virgile Rennard, Guokan Shang, Julie Hunter, Michalis Vazirgiannis
A system that could reliably identify and sum up the most important points of a conversation would be valuable in a wide variety of real-world contexts, from business meetings to medical consultations to customer service calls.
Abstractive Dialogue Summarization Abstractive Text Summarization +2
no code implementations • 1 Dec 2021 • Hadi Abdine, Yanzhu Guo, Moussa Kamal Eddine, Giannis Nikolentzos, Stamatis Outsios, Guokan Shang, Christos Xypolopoulos, Michalis Vazirgiannis
DaSciM (Data Science and Mining) part of LIX at Ecole Polytechnique, established in 2013 and since then producing research results in the area of large scale data analysis via methods of machine and deep learning.
1 code implementation • 16 Oct 2021 • Moussa Kamal Eddine, Guokan Shang, Antoine J. -P. Tixier, Michalis Vazirgiannis
While traditional natural language generation metrics are fast, they are not very reliable.
4 code implementations • COLING 2020 • Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis, Jean-Pierre Lorré
CRF models the conditional probability of the target DA label sequence given the input utterance sequence.
1 code implementation • Asian Chapter of the Association for Computational Linguistics 2020 • Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis, Jean-Pierre Lorré
Abstractive community detection is an important spoken language understanding task, whose goal is to group utterances in a conversation according to whether they can be jointly summarized by a common abstractive sentence.
4 code implementations • ACL 2018 • Guokan Shang, Wensi Ding, Zekun Zhang, Antoine Jean-Pierre Tixier, Polykarpos Meladianos, Michalis Vazirgiannis, Jean-Pierre Lorré
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations.
Ranked #1 on Meeting Summarization on ICSI Meeting Corpus
Abstractive Dialogue Summarization Abstractive Text Summarization +6