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20172022
most citedSelection Bias in News Coverage: Learning it, Fighting it

20 citations · 128 across the 19 of their papers we have counts for

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8 papers · 1 filter

cs.CL2022

An Efficient Active Learning Pipeline for Legal Text Classification

Sepideh Mamooler, Rémi Lebret, Stéphane Massonnet +1

Active Learning (AL) is a powerful tool for learning with less labeled data, in particular, for specialized domains, like legal documents, where unlabeled data is abundant, but the…

cs.CL202110 cited

SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking

Panayiotis Smeros, Carlos Castillo, Karl Aberer

This paper describes SciClops, a method to help combat online scientific misinformation. Although automated fact-checking methods have gained significant attention recently, they r…

cs.CL20215 cited

Legal Transformer Models May Not Always Help

Saibo Geng, Rémi Lebret, Karl Aberer

Deep learning-based Natural Language Processing methods, especially transformers, have achieved impressive performance in the last few years. Applying those state-of-the-art NLP me…

cs.CL20215 cited

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

Klaudia Bałazy, Mohammadreza Banaei, Rémi Lebret +2

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

cs.CL2020

Spoken dialect identification in Twitter using a multi-filter architecture

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. Our model outputs…

cs.CL2019

Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task

Alireza Mohammadshahi, Remi Lebret, Karl Aberer

In this paper, we propose a new approach to learn multimodal multilingual embeddings for matching images and their relevant captions in two languages. We combine two existing objec…