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Improving Medical Care for Adults with Intellectual Disabilities (ID): Can Automated Processing of Electronic Health Record Clinical Text Assist in ID Detection Among the General Outpatient Population?

Rijs, Joyce (author)

<b>Background</b>: Undetected Intellectual Disability (ID) can lead to chronic stress due to overestimation by society. Chronic stress can cause stress-related health issues, like hypertension, chronic fatigue and abdominal complaints. When a physician (General Practitioner (GP) or medical specialist) does not recognize that a patient has ID,...

master thesis 2024

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What would Jiminy Cricket do?: A pluralist approach in generating and processing morally-aligned text

Timmerman, Kirsten (author)

When making decisions, people are automatically guided by their moral compass. However, AI agents need to be conditioned in order to be steered towards moral behaviour. An environment that can be used to train and test agents is the Jiminy Cricket environment. The Jiminy Cricket environment consists of a set of text-based narrative games, where...

bachelor thesis 2023

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Natural Language Processing and Reinforcement Learning to Generate Morally Aligned Text: Comparing a moral agent to an optimally playing agent

Lubbers, Rob (author)

Nowadays Large Language Models are becoming more and more prevalent in today's society. These models act without a sense of morality however. They only prioritize accomplishing their goal. Currently, little research has been done evaluating these models. The current state of the art Reinforcement Learning models represent morality by a singular...

bachelor thesis 2023

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Balancing multidimensional morality and progression: Evaluating the tradeoff for artificial agents playing text-based games

Şerbănescu, Bianca (author)

Morality is a fundamental concept that guides humans in the decision-making process. Given the rise of large language models in society, it is necessary to ensure that they adhere to human principles, among which morality is of substantial importance. While research has been done regarding artificial agents behaving morally, current state of the...

bachelor thesis 2023

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

Parankusam, Taneshwar Pranav (author)

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...

bachelor thesis 2023

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A Comparison of Instance Attribution Methods: Comparing Instance Attribution Methods to Baseline k-Nearest Neighbors Method

de Kruif, Evan (author)

In this research, a comparison between different Instance Attribution (IA) methods and k-Nearest Neighbors (kNN) via cosine similarity is conducted on a Natural Language Processing (NLP) machine learning model. The format in which the comparison is made is by way of a human survey and automated similarity comparisons of representative vectors....

bachelor thesis 2023

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An Empirical Assessment on the Limits of Binary Code Summarization with Transformer-based Models

Al-Kaswan, Ali (author)

Reverse engineering binaries is required to understand and analyse programs for which the source code is unavailable. Decompilers can transform the largely unreadable binaries into a more readable source code-like representation. However, many aspects of source code, such as variable names and comments, are lost during the compilation and...

master thesis 2022

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Toward Fine-grained Causality Reasoning and Question Answering

Wang, Zhen (author)

This thesis mainly studies the causality in natural language processing. Understanding causality is key to the success of NLP applications, especially in high-stakes domains. Causality comes in various perspectives such as enable and prevent that, despite their importance, have been largely ignored in the literature. In view of the lack of a...

master thesis 2022

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Obtaining Query-specific Similar Concepts with BERT-based retrieval for Commonsense Knowledge Gameboard

van Woensel, Martijn (author)

Commonsense knowledge based question answer- ing is a recent topic that has seen a surge in inter- est. Yet most models obtain general data, this pa- per looks at obtaining query-specific similar con- cepts using first and second-order proximity to- gether with BERT-based retrieval. Using these query-specific concepts new commonsense knowl- edge...

bachelor thesis 2022

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Evaluation of natural language processing embeddings in protein function prediction for bacteria

Cosma, Bianca (author)

<b>Motivation: </b>The development of automated protein function prediction models is essential in closing the gap between the large amount of protein sequence data available and the fraction of validly annotated data. Recent approaches to function prediction rely on unsupervised deep learning models, through which protein sequences are...

bachelor thesis 2022

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Bringing digital scribes into orthopedic consultations: Towards AI-assisted clinical documentation

Magyari, Reka (author)

Clinical documentation takes up 40% of clinicians’ time. To ease the administrative burden of clinicians, digital scribes offer the potential to automate clinical note taking. Digital scribes are intelligent documentation softwares that combine automated speech recognition (ASR) and natural language processing (NLP). Digital scribes transcribe...

master thesis 2022

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Cities for Citizens: Identification of Public Values and their Conflicts in Urban Space

Herzog, Rico (author)

In the wake of more inclusive and sustainable cities, as targeted in the UN’s Sustainable Development Goal 11, public administrators and urban planners aspire to incorporate the pluralism of public values into decision making. Although theoretical work exists since the 1990, public values and their conflicts are yet to be empirically identified...

master thesis 2021

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Evaluating catastrophic forgetting of state-of-the-art NLP models for predicting moral values

Arsene, Florentin (author)

Personal moral values represent the motivation behind individuals' actions and opinions. Understanding these values is helpful both in predicting individuals' actions, such as violent protests, and building AI that can better collaborate with humans. Predicting moral values is a challenging problem due to the abstract and subjective essence of...

bachelor thesis 2021

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Evaluating interpretability of state-of-the-art NLP models for predicting moral values

Constantinescu, Ionut (author)

Understanding personal values is a crucial aspect that can facilitate the collaboration between AI and humans. Nonetheless, the implementation of collaborative agents in real life greatly depends on the amount of trust that is built in their relationship with people. In order to bridge this gap, more extensive analysis of the explainability of...

bachelor thesis 2021

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

Vecerdea, Dragos (author)

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...

bachelor thesis 2021

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Estimating the transferability of state-of-the-art models in predicting moral values

Dondera, Alin (author)

Moral values play a crucial role in our decision-making process by defining what is right and wrong. With the emergence of political activism and moral discourse on social media, and the latest developments in Natural Language Processing, we are looking at an opportunity to analyze moral values to observe trends as they form. Recent studies have...

bachelor thesis 2021

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Active Learning To Reduce Human Labeling For Automatic Psychological Text Classification

O'Dwyer Wha Binda, Jahson (author)

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...

bachelor thesis 2021

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Preparing Stance Detection: Feature Extraction Methods and Their Performance Used for Feature-Based Machine Learning Algorithms

Vass, Kristóf (author)

Stance detection is a Natural Language Processing task that aims to detect the stance (support, agreement, or disagreement) of a piece of text towards some target. In this paper, we aim to find the best performing pair of feature extraction method and feature-based machine learning algorithm. By doing so, an explainable method can be found to...

bachelor thesis 2021

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Automatic schema classification for Schema-Focused Therapy using k-Nearest Neighbour

Han, Budi (author)

Personality disorders affect 1 in 7 adults reducing their quality of life. Schema-focused therapy (SFT) has become very popular in Psychotherapy in the treatment of personality disorders (PD), unfortunately there is still in increasing societal need for such mental healthcare. Automation in the assessment of SFT allows for Ecological Momentary...

bachelor thesis 2021

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Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language

Wang, Zina (author)

Relation extraction has been considered as one of the most popular topics nowadays, thanks for its common application in knowledge graph, machine reading and other artificial intelligence sub-field. However, this field has long been suffered from data hunger. Annotating large high-quality datasets for relation extraction is troublesome and time...

master thesis 2020