no code implementations • WS 2017 • Elena Lloret, Ester Boldrini, Patricio Mart{\'\i}nez-Barco, Manuel Palomar
The electronic Word of Mouth has become the most powerful communication channel thanks to the wide usage of the Social Media.
no code implementations • WS 2017 • George Giannakopoulos, John Conroy, Jeff Kubina, Peter A. Rankel, Elena Lloret, Josef Steinberger, Marina Litvak, Benoit Favre
In this brief report we present an overview of the MultiLing 2017 effort and workshop, as implemented within EACL 2017.
no code implementations • WS 2017 • Cristina Barros, Dimitra Gkatzia, Elena Lloret
We present a novel supervised approach to inflection generation for verbs in Spanish.
no code implementations • WS 2017 • Cristina Barros, Dimitra Gkatzia, Elena Lloret
We present a flexible Natural Language Generation approach for Spanish, focused on the surface realisation stage, which integrates an inflection module in order to improve the naturalness and expressivity of the generated language.
no code implementations • RANLP 2019 • Tatiana Vodolazova, Elena Lloret
We analyzed the generated summaries in terms of lexical, syntactic and length-based features of readability, and concluded that summary complexity depends on the compression rate, summarization technique and the nature of the summarized corpus.
no code implementations • RANLP 2019 • Tatiana Vodolazova, Elena Lloret
In this paper we describe how an abstractive text summarization method improved the informativeness of automatic summaries by integrating syntactic text simplification, subject-verb-object concept frequency scoring and a set of rules that transform text into its semantic representation.
1 code implementation • Natural Language & Information Systems 2021 • Robiert Sepúlveda-Torres, Marta Vicente, Estela Saquete, Elena Lloret, Manuel Palomar
It is especially remarkable that the proposed approach, which uses only the relevant information provided by the automatic summaries instead of the full text, is able to classify the different stance categories with very competitive results, so it can be concluded that the use of the automatic extractive summaries has a positive impact for determining the stance of very short information (i. e., headline, sentence) with respect to its whole content.
Ranked #1 on Fake News Detection on FNC-1
no code implementations • EAMT 2022 • Anabela Barreiro, José GC de Souza, Albert Gatt, Mehul Bhatt, Elena Lloret, Aykut Erdem, Dimitra Gkatzia, Helena Moniz, Irene Russo, Fabio Kepler, Iacer Calixto, Marcin Paprzycki, François Portet, Isabelle Augenstein, Mirela Alhasani
This paper presents the Multitask, Multilingual, Multimodal Language Generation COST Action – Multi3Generation (CA18231), an interdisciplinary network of research groups working on different aspects of language generation.