Search Results for author: Rémi Lebret

Found 17 papers, 4 papers with code

Multilingual Text Summarization on Financial Documents

no code implementations FNP (LREC) 2022 Negar Foroutan, Angelika Romanou, Stéphane Massonnet, Rémi Lebret, Karl Aberer

The language models were fine-tuned on a financial document collection of three languages (English, Spanish, and Greek) and aim to identify the beginning of the summary narrative part of the document.

Abstractive Text Summarization

AdaGrid: Adaptive Grid Search for Link Prediction Training Objective

1 code implementation30 Mar 2022 Tim Poštuvan, Jiaxuan You, Mohammadreza Banaei, Rémi Lebret, Jure Leskovec

To mitigate these limitations, we propose Adaptive Grid Search (AdaGrid), which dynamically adjusts the edge message ratio during training.

BIG-bench Machine Learning Link Prediction

Legal Transformer Models May Not Always Help

no code implementations14 Sep 2021 Saibo Geng, Rémi Lebret, Karl Aberer

This work investigates the value of domain adaptive pre-training and language adapters in legal NLP tasks.

Direction is what you need: Improving Word Embedding Compression in Large Language Models

1 code implementation ACL (RepL4NLP) 2021 Klaudia Bałazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor, Karl Aberer

The adoption of Transformer-based models in natural language processing (NLP) has led to great success using a massive number of parameters.

Language Modelling

Spoken dialect identification in Twitter using a multi-filter architecture

no code implementations5 Jun 2020 Mohammadreza Banaei, Rémi Lebret, Karl Aberer

This paper presents our approach for SwissText & KONVENS 2020 shared task 2, which is a multi-stage neural model for Swiss German (GSW) identification on Twitter.

Dialect Identification

Weakly Supervised Active Learning with Cluster Annotation

no code implementations31 Dec 2018 Fábio Perez, Rémi Lebret, Karl Aberer

In this work, we introduce a novel framework that employs cluster annotation to boost active learning by reducing the number of human interactions required to train deep neural networks.

Active Learning

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

2 code implementations7 Feb 2018 Hamza Harkous, Kassem Fawaz, Rémi Lebret, Florian Schaub, Kang G. Shin, Karl Aberer

Companies, users, researchers, and regulators still lack usable and scalable tools to cope with the breadth and depth of privacy policies.

Language Modelling Question Answering

Taxonomy Induction using Hypernym Subsequences

no code implementations25 Apr 2017 Amit Gupta, Rémi Lebret, Hamza Harkous, Karl Aberer

We propose a novel, semi-supervised approach towards domain taxonomy induction from an input vocabulary of seed terms.

"The Sum of Its Parts": Joint Learning of Word and Phrase Representations with Autoencoders

no code implementations18 Jun 2015 Rémi Lebret, Ronan Collobert

We evaluate the quality of the word representations on several classical word evaluation tasks, and we introduce a novel task to evaluate the quality of the phrase representations.

Phrase-based Image Captioning

no code implementations12 Feb 2015 Rémi Lebret, Pedro O. Pinheiro, Ronan Collobert

Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing.

Image Captioning Language Modelling

N-gram-Based Low-Dimensional Representation for Document Classification

no code implementations19 Dec 2014 Rémi Lebret, Ronan Collobert

The number of features is therefore dramatically reduced and documents can be represented as bag of semantic concepts.

Classification Document Classification +3

Rehabilitation of Count-based Models for Word Vector Representations

no code implementations16 Dec 2014 Rémi Lebret, Ronan Collobert

We present a systematic study of the use of the Hellinger distance to extract semantic representations from the word co-occurence statistics of large text corpora.

Dimensionality Reduction Word Embeddings +1

Word Emdeddings through Hellinger PCA

no code implementations19 Dec 2013 Rémi Lebret, Ronan Collobert

Word embeddings resulting from neural language models have been shown to be successful for a large variety of NLP tasks.

NER Word Embeddings

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