activity
20182021
most citedUnlexicalized Transition-based Discontinuous Constituency Parsing

2 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL20212 cited

Learning to Match Mathematical Statements with Proofs

Maximin Coavoux, Shay B. Cohen

We introduce a novel task consisting in assigning a proof to a given mathematical statement. The task is designed to improve the processing of research-level mathematical texts. Ap…

cs.CL20201 cited

Self-Supervised and Controlled Multi-Document Opinion Summarization

Hady Elsahar, Maximin Coavoux, Matthias Gallé +1

We address the problem of unsupervised abstractive summarization of collections of user generated reviews with self-supervision and control. We propose a self-supervised setup that…

cs.CL2019

FlauBERT: Unsupervised Language Model Pre-training for French

Hang Le, Loïc Vial, Jibril Frej +7

Language models have become a key step to achieve state-of-the art results in many different Natural Language Processing (NLP) tasks. Leveraging the huge amount of unlabeled texts…

cs.CL2019

Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic Oracle

Maximin Coavoux, Shay B. Cohen

We introduce a novel transition system for discontinuous constituency parsing. Instead of storing subtrees in a stack --i.e. a data structure with linear-time sequential access-- t…

cs.CL20192 cited

Unlexicalized Transition-based Discontinuous Constituency Parsing

Maximin Coavoux, Benoît Crabbé, Shay B. Cohen

Lexicalized parsing models are based on the assumptions that (i) constituents are organized around a lexical head (ii) bilexical statistics are crucial to solve ambiguities. In thi…

cs.CL2018

Privacy-preserving Neural Representations of Text

Maximin Coavoux, Shashi Narayan, Shay B. Cohen

This article deals with adversarial attacks towards deep learning systems for Natural Language Processing (NLP), in the context of privacy protection. We study a specific type of a…