37 citations · 66 across the 7 of their papers we have counts for
15 papers
Hyperplane bounds for neural feature mappings
Antonio Jimeno Yepes
Deep learning methods minimise the empirical risk using loss functions such as the cross entropy loss. When minimising the empirical risk, the generalisation of the learnt function…
ICDAR 2021 Competition on Scientific Literature Parsing
Antonio Jimeno Yepes, Xu Zhong, Douglas Burdick
Scientific literature contain important information related to cutting-edge innovations in diverse domains. Advances in natural language processing have been driving the fast devel…
Grey-box Adversarial Attack And Defence For Sentiment Classification
Ying Xu, Xu Zhong, Antonio Jimeno Yepes +1
We introduce a grey-box adversarial attack and defence framework for sentiment classification. We address the issues of differentiability, label preservation and input reconstructi…
Single versus Multiple Annotation for Named Entity Recognition of Mutations
David Martinez Iraola, Antonio Jimeno Yepes
The focus of this paper is to address the knowledge acquisition bottleneck for Named Entity Recognition (NER) of mutations, by analysing different approaches to build manually-anno…
Understanding in Artificial Intelligence
Stefan Maetschke, David Martinez Iraola, Pieter Barnard +4
Current Artificial Intelligence (AI) methods, most based on deep learning, have facilitated progress in several fields, including computer vision and natural language understanding…
Elephant in the Room: An Evaluation Framework for Assessing Adversarial Examples in NLP
Ying Xu, Xu Zhong, Antonio Jose Jimeno Yepes +1
An adversarial example is an input transformed by small perturbations that machine learning models consistently misclassify. While there are a number of methods proposed to generat…