Natural Language Processing and Tabular Data sets in Federated Continual Learning: A usability study of FCL in domains beyond Image classification

Federated Continual Learning (FCL) is a emerging field with strong roots in Image classification. However, limited research has been done on its potential in Natural Language Processing and Tabular datasets. With recent developments in A.I. with language models and the widespread use of mobile devices, it becomes relevant to consider FCL’s...

The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing

Although popular and effective, large language models (LLM) are characterised by a performance vs. transparency trade-off that hinders their applicability to sensitive scenarios. This is the main reason behind many approaches focusing on local post-hoc explanations recently proposed by the XAI community. However, to the best of our knowledge,...

CatIss: An Intelligent Tool for Categorizing Issues Reports using Transformers

Users use Issue Tracking Systems to keep track and manage issue reports in their repositories. An issue is a rich source of software information that contains different reports including a problem, a request for new features, or merely a question about the software product. As the number of these issues increases, it becomes harder to manage...

Moral Embeddings: A closer look at their Performance, Generalizability and Transferability

Moral values are abstract ideas that ground our judgements towards what is right or wrong. However, with the rapid unfold of moral rhetoric on social media, it becomes increasingly important to place these ideas in a moral frame, contain their harmful effects, and recognise their positive ones. So far, estimating values from opinionated text has...

Active Learning To Reduce Human Labeling For Automatic Psychological Text Classification

In recent years there has been an increase in the number of patients for issues relating to mental illness. To this effect to help with this increase, schema mode assessment through a conversation agent is being used to conduct schema therapy, a form of psychological treatment. To train such an agent, training data labeled by humans is necessary...

WHOSe Heritage: Classification of UNESCO World Heritage Statements of "outstanding Universal Value" with Soft Labels

The UNESCO World Heritage List (WHL) includes the exceptionally valuable cultural and natural heritage to be preserved for mankind. Evaluating and justifying the Outstanding Universal Value (OUV) is essential for each site inscribed in the WHL, and yet a complex task, even for experts, since the selection criteria of OUV are not mutually...

Extracting location context from transcripts: a comparison of ELMo and TF-IDF

Using transcripts of the TV-series FRIENDS, this paper explores the problem of predicting the location in which a sentence was said. The research focuses on using feature extraction on the sentences, and training a logistic regression model on those features. Specifically looking at the differences in performance between using ELMo and TF-IDF...

Using Skip-Gram Model to Predict from which Show a Given Line is

Text classification has a wide range of usage such as extracting the sentiment out of a product review, analyzing the topic of a document and spam detection. In this research, the text classification task is to predict from which TV-show a given line is. The skip-gram model, originally used to train the Word2Vec sentence embeddings [Mikolov et...

Recognizing and Handling Negations in Machine Learning

In several machine learning problems, a relatively small subproblem is present in which combinations of (negating) objects or structures result in a negation or otherwise other classification compared to when these (negating) objects are not present. To be more specific, a variant of the XOR problem is present in a small amount of objects in...