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Found 13 papers, 5 papers with code
How’s Business Going Worldwide ? A Multilingual Annotated Corpus for Business Relation Extraction
The business world has changed due to the 21st century economy, where borders have melted and trades became free.
Improving Composition of Sentence Embeddings through the Lens of Statistical Relational Learning
In this work, we show that textual relational models implicitly use compositions from baseline SRL models.
Load What You Need: Smaller Versions of Mutililingual BERT
The obtained results confirm that we can generate smaller models that keep comparable results, while reducing up to 45% of the total number of parameters.
Load What You Need: Smaller Versions of Multilingual BERT
The obtained results confirm that we can generate smaller models that keep comparable results, while reducing up to 45% of the total number of parameters.
DiscSense: Automated Semantic Analysis of Discourse Markers
In this work, we take another perspective: using a model trained to predict discourse markers between sentence pairs, we predict plausible markers between sentence pairs with a known semantic relation (provided by existing classification datasets).
A Pragmatics-Centered Evaluation Framework for Natural Language Understanding
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 representations.
Aprentissage non-supervis\'e pour l'appariement et l'\'etiquetage de cas cliniques en fran\ccais - DEFT2019 (Unsupervised learning for matching and labelling of french clincal cases - DEFT2019 )
Nous pr{\'e}sentons le syst{\`e}me utilis{\'e} par l{'}{\'e}quipe Synapse/IRIT dans la comp{\'e}tition DEFT2019 portant sur deux t{\^a}ches li{\'e}es {\`a} des cas cliniques r{\'e}dig{\'e}s en fran{\c{c}}ais : l{'}une d{'}appariement entre des cas cliniques et des discussions, l{'}autre d{'}extraction de mots-clefs.
Composition of Sentence Embeddings: Lessons from Statistical Relational Learning
In this article, we show that previous work on relation prediction between texts implicitly uses compositions from baseline SRL models.
Composition of Sentence Embeddings:Lessons from Statistical Relational Learning
In this article, we show that previous work on relation prediction between texts implicitly uses compositions from baseline SRL models.
Mining Discourse Markers for Unsupervised Sentence Representation Learning
Current state of the art systems in NLP heavily rely on manually annotated datasets, which are expensive to construct.
Ranked #1 on
Relation Classification
on Discovery
Concat\'enation de r\'eseaux de neurones pour la classification de tweets, DEFT2018 (Concatenation of neural networks for tweets classification, DEFT2018 )
Nous pr{\'e}sentons le syst{\`e}me utilis{\'e} par l{'}{\'e}quipe Melodi/Synapse D{\'e}veloppement dans la comp{\'e}tition DEFT2018 portant sur la classification de th{\'e}matique ou de sentiments de tweets en fran{\c{c}}ais.
Synapse at CAp 2017 NER challenge: Fasttext CRF
We present our system for the CAp 2017 NER challenge which is about named entity recognition on French tweets.
Changement stylistique de phrases par apprentissage faiblement supervis\'e (Textual Style Transfer using Weakly Supervised Learning)
Plusieurs t{\^a}ches en traitement du langage naturel impliquent de modifier des phrases en conservant au mieux leur sens, comme la reformulation, la compression, la simplification, chacune avec leurs propres donn{\'e}es et mod{\`e}les.
