8 citations · 13 across the 4 of their papers we have counts for
6 papers · 1 filter
Languages You Know Influence Those You Learn: Impact of Language Characteristics on Multi-Lingual Text-to-Text Transfer
Benjamin Muller, Deepanshu Gupta, Siddharth Patwardhan +3
Multi-lingual language models (LM), such as mBERT, XLM-R, mT5, mBART, have been remarkably successful in enabling natural language tasks in low-resource languages through cross-lin…
First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
Benjamin Muller, Yanai Elazar, Benoît Sagot +1
Multilingual pretrained language models have demonstrated remarkable zero-shot cross-lingual transfer capabilities. Such transfer emerges by fine-tuning on a task of interest in on…
When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models
Benjamin Muller, Antonis Anastasopoulos, Benoît Sagot +1
Transfer learning based on pretraining language models on a large amount of raw data has become a new norm to reach state-of-the-art performance in NLP. Still, it remains unclear h…
Establishing a New State-of-the-Art for French Named Entity Recognition
Pedro Javier Ortiz Suárez, Yoann Dupont, Benjamin Muller +2
The French TreeBank developed at the University Paris 7 is the main source of morphosyntactic and syntactic annotations for French. However, it does not include explicit informatio…
Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi
Benjamin Muller, Benoit Sagot, Djamé Seddah
Building natural language processing systems for non standardized and low resource languages is a difficult challenge. The recent success of large-scale multilingual pretrained lan…
CamemBERT: a Tasty French Language Model
Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez +5
Pretrained language models are now ubiquitous in Natural Language Processing. Despite their success, most available models have either been trained on English data or on the concat…