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.
1 code implementation • 8 Feb 2023 • Mohammadreza Banaei, Klaudia Bałazy, Artur Kasymov, Rémi Lebret, Jacek Tabor, Karl Aberer
Recent transformer language models achieve outstanding results in many natural language processing (NLP) tasks.
no code implementations • 28 Nov 2022 • Alexander Glavackij, Dimitri Percia David, Alain Mermoud, Angelika Romanou, Karl Aberer
Our autoencoder approach improves the MAPE by 13. 5% on average over the second-best result.
no code implementations • 15 Nov 2022 • Sepideh Mamooler, Rémi Lebret, Stéphane Massonnet, Karl Aberer
However, most AL strategies require a set of labeled samples to start with, which is expensive to acquire.
1 code implementation • 11 Nov 2022 • Thanh Trung Huynh, Minh Hieu Nguyen, Thanh Tam Nguyen, Phi Le Nguyen, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer
Advances in deep neural network (DNN) architectures have enabled new prediction techniques for stock market data.
1 code implementation • 25 May 2022 • Negar Foroutan, Mohammadreza Banaei, Remi Lebret, Antoine Bosselut, Karl Aberer
Multilingual pre-trained language models transfer remarkably well on cross-lingual downstream tasks.
no code implementations • 9 Dec 2021 • Chi Thang Duong, Dimitri Percia David, Ljiljana Dolamic, Alain Mermoud, Vincent Lenders, Karl Aberer
This is a two-task setup involving (i) technology classification of entities extracted from company corpus, and (ii) technology and company retrieval based on classified technologies.
no code implementations • 25 Oct 2021 • Panayiotis Smeros, Carlos Castillo, Karl Aberer
This paper describes SciClops, a method to help combat online scientific misinformation.
no code implementations • 14 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.
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.
no code implementations • 12 Apr 2021 • Angelika Romanou, Panayiotis Smeros, Karl Aberer
In this work, we present a methodology for creating scientific news article representations by modeling the directed graph between the scientific news articles and the cited scientific publications.
no code implementations • 27 Aug 2020 • Angelika Romanou, Panayiotis Smeros, Carlos Castillo, Karl Aberer
We demonstrate the SciLens News Platform, a novel system for evaluating the quality of news articles.
no code implementations • 5 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.
no code implementations • 23 Apr 2020 • Fangyu Liu, Rémi Lebret, Didier Orel, Philippe Sordet, Karl Aberer
The system fuses multiple textual sources extracted from news articles and accepts multilingual inputs.
no code implementations • 20 Nov 2019 • Chi Thang Duong, Thanh Dat Hoang, Ha The Hien Dang, Quoc Viet Hung Nguyen, Karl Aberer
Graph neural network (GNN) is a deep model for graph representation learning.
1 code implementation • EMNLP (WS) 2019 • 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.
no code implementations • 25 Sep 2019 • Chi Thang Duong, Dung Hoang, Truong Giang Le Ba, Thanh Le Cong, Hongzhi Yin, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer
We provide empirical evidence that the communities learned by DMC are meaningful and that the node embeddings are competitive in different node classification benchmarks.
no code implementations • 6 Sep 2019 • Chi Thang Duong, Hongzhi Yin, Thanh Dat Hoang, Truong Giang Le Ba, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer
We therefore propose a framework for parallel computation of a graph embedding using a cluster of compute nodes with resource constraints.
no code implementations • 13 Mar 2019 • Panayiotis Smeros, Carlos Castillo, Karl Aberer
Based on these aspects, we describe a series of indicators of news quality.
no code implementations • 31 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.
2 code implementations • 7 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.
no code implementations • 7 Aug 2017 • Chi Thang Duong, Remi Lebret, Karl Aberer
Although information on social media can be of different modalities such as texts, images, audio or videos, traditional approaches in classification usually leverage only one prominent modality.
no code implementations • 25 Apr 2017 • Amit Gupta, Rémi Lebret, Hamza Harkous, Karl Aberer
We propose a simple, yet effective, approach towards inducing multilingual taxonomies from Wikipedia.
no code implementations • 25 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.
no code implementations • 26 Dec 2016 • Tian Guo, Zhao Xu, Xin Yao, Haifeng Chen, Karl Aberer, Koichi Funaya
Time series forecasting for streaming data plays an important role in many real applications, ranging from IoT systems, cyber-networks, to industrial systems and healthcare.
no code implementations • 22 Aug 2013 • Tri Kurniawan Wijaya, Kate Larson, Karl Aberer
Recent work has suggested reducing electricity generation cost by cutting the peak to average ratio (PAR) without reducing the total amount of the loads.