Search Results for author: Elena Lloret

Found 13 papers, 1 papers with code

MultiLing 2017 Overview

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.

Document Summarization

Improving the Naturalness and Expressivity of Language Generation for 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.

Text Generation

Towards Adaptive Text Summarization: How Does Compression Rate Affect Summary Readability of L2 Texts?

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.

Abstractive Text Summarization

The Impact of Rule-Based Text Generation on the Quality of Abstractive Summaries

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.

Abstractive Text Summarization Informativeness +2

Exploring Summarization to Enhance Headline Stance Detection

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.

Fake News Detection Misinformation +2

Multi3Generation: Multitask, Multilingual, Multimodal Language Generation

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.

Text Generation

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