Search Results for author: Jo{\~a}o Ant{\'o}nio Rodrigues

Found 8 papers, 2 papers with code

Reproduction and Revival of the Argument Reasoning Comprehension Task

no code implementations LREC 2020 Jo{\~a}o Ant{\'o}nio Rodrigues, Ruben Branco, Jo{\~a}o Silva, Ant{\'o}nio Branco

Given a recent publication that pointed out spurious statistical cues in the data set used in the shared task, and that produced a revised version of it, we also evaluated the reproduced systems with this new data set.

Predicting Brain Activation with WordNet Embeddings

1 code implementation WS 2018 Jo{\~a}o Ant{\'o}nio Rodrigues, Ruben Branco, Jo{\~a}o Silva, Chakaveh Saedi, Ant{\'o}nio Branco

The task of taking a semantic representation of a noun and predicting the brain activity triggered by it in terms of fMRI spatial patterns was pioneered by Mitchell et al. 2008.

Word Embeddings

Ways of Asking and Replying in Duplicate Question Detection

no code implementations SEMEVAL 2017 Jo{\~a}o Ant{\'o}nio Rodrigues, Chakaveh Saedi, Vladislav Maraev, Jo{\~a}o Silva, Ant{\'o}nio Branco

This paper presents the results of systematic experimentation on the impact in duplicate question detection of different types of questions across both a number of established approaches and a novel, superior one used to address this language processing task.

Machine Translation Question Answering +1

Use of Domain-Specific Language Resources in Machine Translation

no code implementations LREC 2016 Sanja {\v{S}}tajner, Andreia Querido, Nuno Rendeiro, Jo{\~a}o Ant{\'o}nio Rodrigues, Ant{\'o}nio Branco

In this paper, we address the problem of Machine Translation (MT) for a specialised domain in a language pair for which only a very small domain-specific parallel corpus is available.

Machine Translation Translation

Bootstrapping a Hybrid MT System to a New Language Pair

no code implementations LREC 2016 Jo{\~a}o Ant{\'o}nio Rodrigues, Nuno Rendeiro, Andreia Querido, Sanja {\v{S}}tajner, Ant{\'o}nio Branco

The usual concern when opting for a rule-based or a hybrid machine translation (MT) system is how much effort is required to adapt the system to a different language pair or a new domain.

Machine Translation Translation

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