Search Results for author:
Found 49 papers, 23 papers with code
SemEval 2022 Task 10: Structured Sentiment Analysis
In this paper, we introduce the first SemEval shared task on Structured Sentiment Analysis, for which participants are required to predict all sentiment graphs in a text, where a single sentiment graph is composed of a sentiment holder, target, expression and polarity.
BasqueGLUE: A Natural Language Understanding Benchmark for Basque
Natural Language Understanding (NLU) technology has improved significantly over the last few years and multitask benchmarks such as GLUE are key to evaluate this improvement in a robust and general way.
A Semantics-Aware Approach to Automated Claim Verification
The influence of fake news in the perception of reality has become a mainstream topic in the last years due to the fast propagation of misleading information.
Benchmarking Meta-embeddings: What Works and What Does Not
In the last few years, several methods have been proposed to build meta-embeddings.
Critical Questions Generation: Motivation and Challenges
The development of Large Language Models (LLMs) has brought impressive performances on mitigation strategies against misinformation, such as counterargument generation.
CasiMedicos-Arg: A Medical Question Answering Dataset Annotated with Explanatory Argumentative Structures
In this paper, we follow this direction, and we present, to the best of our knowledge, the first multilingual dataset for Medical Question Answering where correct and incorrect diagnoses for a clinical case are enriched with a natural language explanation written by doctors.
Argument Mining in Data Scarce Settings: Cross-lingual Transfer and Few-shot Techniques
Contrary to previous work, we show that for Argument Mining data transfer obtains better results than model-transfer and that fine-tuning outperforms few-shot methods.
A LLM-Based Ranking Method for the Evaluation of Automatic Counter-Narrative Generation
This paper proposes a novel approach to evaluate Counter Narrative (CN) generation using a Large Language Model (LLM) as an evaluator.
Political Leaning Inference through Plurinational Scenarios
Social media users express their political preferences via interaction with other users, by spontaneous declarations or by participation in communities within the network.
Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain
While these LLMs display competitive performance on automated medical texts benchmarks, they have been pre-trained and evaluated with a focus on a single language (English mostly).
Meta4XNLI: A Crosslingual Parallel Corpus for Metaphor Detection and Interpretation
Metaphors, although occasionally unperceived, are ubiquitous in our everyday language.
MedExpQA: Multilingual Benchmarking of Large Language Models for Medical Question Answering
So far the benchmark is available in four languages, but we hope that this work may encourage further development to other languages.
Evaluating Shortest Edit Script Methods for Contextual Lemmatization
We experiment with seven languages of different morphological complexity, namely, English, Spanish, Basque, Russian, Czech, Turkish and Polish, using multilingual and language-specific pre-trained masked language encoder-only models as a backbone to build our lemmatizers.
Basque and Spanish Counter Narrative Generation: Data Creation and Evaluation
Being a parallel corpus, also with respect to the original English CONAN, it allows to perform novel research on multilingual and crosslingual automatic generation of CNs.
Explanatory Argument Extraction of Correct Answers in Resident Medical Exams
Comprehensive experimentation with language models for Spanish shows that sometimes multilingual models fare better than monolingual ones, even outperforming models which have been adapted to the medical domain.
Optimal Strategies to Perform Multilingual Analysis of Social Content for a Novel Dataset in the Tourism Domain
Extensive experimentation on a newly collected and annotated multilingual (French, English, and Spanish) dataset composed of tourism-related tweets shows that current few-shot learning techniques allow us to obtain competitive results for all three tasks with very little annotation data: 5 tweets per label (15 in total) for Sentiment Analysis, 10% of the tweets for location detection (around 160) and 13% (200 approx.)
GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction
In this paper, we propose GoLLIE (Guideline-following Large Language Model for IE), a model able to improve zero-shot results on unseen IE tasks by virtue of being fine-tuned to comply with annotation guidelines.
Ranked #1 on
Zero-shot Named Entity Recognition (NER)
on HarveyNER
(using extra training data)
HiTZ@Antidote: Argumentation-driven Explainable Artificial Intelligence for Digital Medicine
Providing high quality explanations for AI predictions based on machine learning is a challenging and complex task.
A Modular Approach for Multilingual Timex Detection and Normalization using Deep Learning and Grammar-based methods
Detecting and normalizing temporal expressions is an essential step for many NLP tasks.
On the Role of Morphological Information for Contextual Lemmatization
Given that the process to obtain a lemma from an inflected word can be explained by looking at its morphosyntactic category, including fine-grained morphosyntactic information to train contextual lemmatizers has become common practice, without considering whether that is the optimum in terms of downstream performance.
Cross-lingual Argument Mining in the Medical Domain
Nowadays the medical domain is receiving more and more attention in applications involving Artificial Intelligence as clinicians decision-making is increasingly dependent on dealing with enormous amounts of unstructured textual data.
T-Projection: High Quality Annotation Projection for Sequence Labeling Tasks
In the absence of readily available labeled data for a given sequence labeling task and language, annotation projection has been proposed as one of the possible strategies to automatically generate annotated data.
Ranked #1 on
Cross-Lingual NER
on MasakhaNER2.0
(Hausa metric)
Lessons learned from the evaluation of Spanish Language Models
Given the impact of language models on the field of Natural Language Processing, a number of Spanish encoder-only masked language models (aka BERTs) have been trained and released.
Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings
Zero-resource cross-lingual transfer approaches aim to apply supervised models from a source language to unlabelled target languages.
Ranked #1 on
Cross-Lingual NER
on CoNLL Spanish
Leveraging a New Spanish Corpus for Multilingual and Crosslingual Metaphor Detection
The lack of wide coverage datasets annotated with everyday metaphorical expressions for languages other than English is striking.
Relational Embeddings for Language Independent Stance Detection
The large majority of the research performed on stance detection has been focused on developing more or less sophisticated text classification systems, even when many benchmarks are based on social network data such as Twitter.
BasqueParl: A Bilingual Corpus of Basque Parliamentary Transcriptions
Parliamentary transcripts provide a valuable resource to understand the reality and know about the most important facts that occur over time in our societies.
Does Corpus Quality Really Matter for Low-Resource Languages?
For instance, 66% of documents are rated as high-quality for EusCrawl, in contrast with <33% for both mC4 and CC100.
Multilingual Counter Narrative Type Classification
The growing interest in employing counter narratives for hatred intervention brings with it a focus on dataset creation and automation strategies.
Semi-automatic Generation of Multilingual Datasets for Stance Detection in Twitter
While interactions in social media such as Twitter occur in many natural languages, research on stance detection (the position or attitude expressed with respect to a specific topic) within the Natural Language Processing field has largely been done for English.
Multilingual Stance Detection in Tweets: The Catalonia Independence Corpus
The TW-10 referendum Dataset released at IberEval 2018 is a previous effort to provide multilingual stance-annotated data in Catalan and Spanish.
Give your Text Representation Models some Love: the Case for Basque
This is suboptimal as, for many languages, the models have been trained on smaller (or lower quality) corpora.
Multilingual Stance Detection: The Catalonia Independence Corpus
The TW-10 Referendum Dataset released at IberEval 2018 is a previous effort to provide multilingual stance-annotated data in Catalan and Spanish.
A Common Semantic Space for Monolingual and Cross-Lingual Meta-Embeddings
This paper presents a new technique for creating monolingual and cross-lingual meta-embeddings.
Doris Martin at SemEval-2019 Task 4: Hyperpartisan News Detection with Generic Semi-supervised Features
In this paper we describe our participation to the Hyperpartisan News Detection shared task at SemEval 2019.
Language Independent Sequence Labelling for Opinion Target Extraction
In this research note we present a language independent system to model Opinion Target Extraction (OTE) as a sequence labelling task.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Real Time Monitoring of Social Media and Digital Press
Crawled data is processed by means of the EliXa Sentiment Analysis system.
EliXa: A Modular and Flexible ABSA Platform
This paper presents a supervised Aspect Based Sentiment Analysis (ABSA) system.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Q-WordNet PPV: Simple, Robust and (almost) Unsupervised Generation of Polarity Lexicons for Multiple Languages
This paper presents a simple, robust and (almost) unsupervised dictionary-based method, qwn-ppv (Q-WordNet as Personalized PageRanking Vector) to automatically generate polarity lexicons.
Multilingual and Cross-lingual Timeline Extraction
In this paper we present an approach to extract ordered timelines of events, their participants, locations and times from a set of multilingual and cross-lingual data sources.
Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised Features
Finally, the results show that our emphasis on clustering features is crucial to develop robust out-of-domain models.
Ranked #61 on
Named Entity Recognition (NER)
on CoNLL 2003 (English)
IXA pipeline: Efficient and Ready to Use Multilingual NLP tools
IXA pipeline is a modular set of Natural Language Processing tools (or pipes) which provide easy access to NLP technology.
Generating Polarity Lexicons with WordNet propagation in 5 languages
In this paper we focus on the creation of general-purpose (as opposed to domain-specific) polarity lexicons in five languages: French, Italian, Dutch, English and Spanish using WordNet propagation.
SUMAT: Data Collection and Parallel Corpus Compilation for Machine Translation of Subtitles
Subtitling and audiovisual translation have been recognized as areas that could greatly benefit from the introduction of Statistical Machine Translation (SMT) followed by post-editing, in order to increase efficiency of subtitle production process.
