activity
20172026
most citedLoad What You Need: Smaller Versions of Multilingual BERT

9 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Reification as a Transferable Vocabulary: Zero-Shot Link Prediction with Vanilla GNNs

Camille Pradel

Knowledge graph foundation models such as ULTRA achieve zero-shot link prediction on unseen graphs through dedicated architectures that hard-code a transfer mechanism. In this work…

cs.CL2020★ 9 cited

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…

cs.CL2020★ 2 cited

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…

cs.CL2019★ 1 cited

A Pragmatics-Centered Evaluation Framework for Natural Language Understanding

Damien Sileo, Tim Van-de-Cruys, Camille Pradel +1

New models for natural language understanding have recently made an unparalleled amount of progress, which has led some researchers to suggest that the models induce universal text…

cs.CL2019

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…

cs.CL2017★ 2 cited

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…