activity
20202022
most citedAraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization

6 citations · 15 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2022

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…

cs.CL2022

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…

cs.CL2022★ 1 cited

Word Sense Induction with Hierarchical Clustering and Mutual Information Maximization

Hadi Abdine, Moussa Kamal Eddine, Michalis Vazirgiannis +1

Word sense induction (WSI) is a difficult problem in natural language processing that involves the unsupervised automatic detection of a word's senses (i.e. meanings). Recent work…

cs.CL2022★ 3 cited

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran +74

Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using…

cs.CL2022★ 6 cited

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…

cs.LG2021

A Highly Effective Low-Rank Compression of Deep Neural Networks with Modified Beam-Search and Modified Stable Rank

Moonjung Eo, Suhyun Kang, Wonjong Rhee

Compression has emerged as one of the essential deep learning research topics, especially for the edge devices that have limited computation power and storage capacity. Among the m…

cs.CL2021★ 4 cited

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…

cs.CL2021★ 1 cited

Evaluation Of Word Embeddings From Large-Scale French Web Content

Hadi Abdine, Christos Xypolopoulos, Moussa Kamal Eddine +1

Distributed word representations are popularly used in many tasks in natural language processing. Adding that pretrained word vectors on huge text corpus achieved high performance…

cs.CL2020

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…