Ponències/Comunicacions de congressos
Recent Submissions
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Combining subword representations into word-level representations in the transformer architecture
(Association for Computational Linguistics, 2020)
Conference lecture
Open AccessIn Neural Machine Translation, using word-level tokens leads to degradation in translation quality. The dominant approaches use subword-level tokens, but this increases the length of the sequences and makes it difficult ... -
A Survey on multimodal data stream mining for e-learner’s emotion recognition
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Restricted access - publisher's policyEmotions play a crucial role in learning. To improve and optimize electronic learning (e-Learning) outcomes, many researchers have investigated the role of emotions. Also, researchers have come up with many approaches to ... -
Augmenting the power of (partial) MaxSat resolution with extension
(AAAI Press, 2020)
Conference lecture
Restricted access - publisher's policyThe refutation power of SAT and MaxSAT resolution is challenged by problems like the soft and hard Pigeon Hole Problem PHP for which short refutations do not exist. In this paper we augment the MaxSAT resolution proof ... -
Textual visual semantic dataset for text spotting
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Open AccessText Spotting in the wild consists of detecting and recognizing text appearing in images (e.g. signboards, traffic signals or brands in clothing or objects). This is a challenging problem due to the complexity of the context ... -
Automatic Spanish translation of SQuAD dataset for multi-lingual question answering
(European Language Resources Association (ELRA), 2020)
Conference lecture
Open AccessRecently, multilingual question answering became a crucial research topic, and it is receiving increased interest in the NLP community.However, the unavailability of large-scale datasets makes it challenging to train ... -
Synthetic dataset generation with itemset-based generative models
(Institute of Electrical and Electronics Engineers (IEEE), 2019)
Conference report
Open AccessThis paper proposes three different data generators, tailored to transactional datasets, based on existing itemset-based generative models. All these generators are intuitive and easy to implement and show satisfactory ... -
Characterizing transactional databases for frequent itemset mining
(CEUR-WS.org, 2019)
Conference report
Open AccessThis paper presents a study of the characteristics of transactional databases used in frequent itemset mining. Such characterizations have typically been used to benchmark and understand the data mining algorithms working ... -
Building graph representations of deep vector embeddings
(Association for Computational Linguistics, 2017)
Conference lecture
Open AccessPatterns stored within pre-trained deep neural networks compose large and powerful descriptive languages that can be used for many different purposes. Typically, deep network representations are implemented within vector ... -
Full-network embedding in a multimodal embedding pipeline
(Association for Computational Linguistics, 2017)
Conference lecture
Open AccessThe current state-of-the-art for image annotation and image retrieval tasks is obtained through deep neural networks, which combine an image representation and a text representation into a shared embedding space. In this ... -
Evaluating the underlying gender bias in contextualized word embeddings
(Association for Computational Linguistics, 2019)
Conference report
Open AccessGender bias is highly impacting natural language processing applications. Word embeddings have clearly been proven both to keep and amplify gender biases that are present in current data sources. Recently, contextualized ... -
Improving accuracy and speeding up document image classification through parallel systems
(Springer, 2020)
Conference report
Open AccessThis paper presents a study showing the benefits of the EfficientNet models compared with heavier Convolutional Neural Networks (CNNs) in the Document Classification task, essential problem in the digitalization process ... -
A Parser-based tool to assist instructors in grading computer graphics assignments
(European Association for Computer Graphics (Eurographics), 2019)
Conference report
Open AccessAlthough online e-learning environments are increasingly used in university courses, manual assessment still dominates the way students are graded. Interactive judges providing a pass/fail verdict based on test sets are ...
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