6 citations · 10 across the 4 of their papers we have counts for
5 papers
Questioning the Validity of Summarization Datasets and Improving Their Factual Consistency
Yanzhu Guo, Chloé Clavel, Moussa Kamal Eddine +1
The topic of summarization evaluation has recently attracted a surge of attention due to the rapid development of abstractive summarization systems. However, the formulation of the…
DATScore: Evaluating Translation with Data Augmented Translations
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. Inspired by the recent…
AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization
Moussa Kamal Eddine, Nadi Tomeh, Nizar Habash +2
Like most natural language understanding and generation tasks, state-of-the-art models for summarization are transformer-based sequence-to-sequence architectures that are pretraine…
FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metricsfor Automatic Text Generation
Moussa Kamal Eddine, Guokan Shang, Antoine J. -P. Tixier +1
Fast and reliable evaluation metrics are key to R&D progress. While traditional natural language generation metrics are fast, they are not very reliable. Conversely, new metrics ba…
BARThez: a Skilled Pretrained French Sequence-to-Sequence Model
Moussa Kamal Eddine, Antoine J. -P. Tixier, Michalis Vazirgiannis
Inductive transfer learning has taken the entire NLP field by storm, with models such as BERT and BART setting new state of the art on countless NLU tasks. However, most of the ava…