2 citations · 4 across the 3 of their papers we have counts for
4 papers
Load What You Need: Smaller Versions of Multilingual BERT
Amine Abdaoui, Camille Pradel, Grégoire Sigel
Pre-trained Transformer-based models are achieving state-of-the-art results on a variety of Natural Language Processing data sets. However, the size of these models is often a draw…
DiscSense: Automated Semantic Analysis of Discourse Markers
Damien Sileo, Tim Van de Cruys, Camille Pradel +1
Discourse markers ({\it by contrast}, {\it happily}, etc.) are words or phrases that are used to signal semantic and/or pragmatic relationships between clauses or sentences. Recent…
Mining Discourse Markers for Unsupervised Sentence Representation Learning
Damien Sileo, Tim Van-De-Cruys, Camille Pradel +1
Current state of the art systems in NLP heavily rely on manually annotated datasets, which are expensive to construct. Very little work adequately exploits unannotated data -- such…
Synapse at CAp 2017 NER challenge: Fasttext CRF
Damien Sileo, Camille Pradel, Philippe Muller +1
We present our system for the CAp 2017 NER challenge which is about named entity recognition on French tweets. Our system leverages unsupervised learning on a larger dataset of Fre…