Natural Language Processing and Reinforcement Learning to Generate Morally: What is the optimal weight w to win the games while playing morally?

In our everyday life, people interact more and more with agents. However these agents often lack a moral sense and prioritize the accomplishment of the given task. In consequence, agents may unknowingly act immorally. Little research or progress has been done to endow agents with human morality and an internal sense of right and wrong. As of...

NLP and reinforcement learning to generate morally aligned text: How does explainable models perform compared to black-box models

<br/>This paper evaluates the performance of an automated explainable model, Moral- Strength, to predict morality, or more pre- cisely Moral Foundations Theory (MFT) traits. MFT is a way to represent and divide morality into precise and detailed traits. This evaluation happens in the Jiminy Cricket environment, an environ- ment composed of 25...

Distil-CodeGPT, Distilling Code-Generation Models for Local Use

The application of large language models (LLMs) for programming tasks, such as automatic code completion, has seen a significant upswing in recent years. However, due to their computational demands, they have to operate on servers. This both requires users to have a steady internet connection and raises potential privacy concerns. Therefore,...

Are BERT-based fact-checking models robust against adversarial attack?

We seek to examine the vulnerability of BERT-based fact-checking. We implement a gradient based, adversarial attack strategy, based on Hotflip swapping individual tokens from the input. We use this on a pre-trained ExPred model for fact-checking. We find that gradient based adversarial attacks are ineffective against ExPred. Uncertainties about...

A Human-In-the-Loop Framework to Assess Multimodal Machine Learning Models

Recent works explain the DNN models that perform image classification tasks following the "attribution, human-in-the-loop, extraction" workflow. However, little work has looked into such an approach for explaining DNN models for language or multimodal tasks. To address this gap, we propose a framework that explains and assesses the model...

Compression of the embedding layer in an LSTM model using tensor train decomposition for NLP

Natural Language Processing (NLP) deals with understanding and processing human text by any computer software. There are several network architectures in the fields of deep learning and artificial intelligence that are used for NLP. Deep learning techniques like recurrent neural networks and feed-forward neural networks are used to develop...

LoveBERT: Leveraging Language Models to Improve Matchmaking at Breeze

Online dating has become the most popular method of finding potential romantic partners. At the core of these platforms, there is a reciprocal recommender system which recommends users to other users on the platform. Breeze is an example of such a dating app, serving its users potential romantic partners every day in the hopes of sending them on...

Loss functions and neural networks: Comparing different loss functions for NLP neural networks

Neural network is an active research field which involves many different (unsolved) issues, for example, different types of configuration of the network architectures, training strategies, etc. Amongst these active issues, the choice of loss (or cost) functions plays an important role in how a neural network model is to be optimized (trained)...

A systematic comparison of commonsense knowledge usages between natural language processing (NLP) and computer vision (CV)

Commonsense knowledge is the key of human intelligence in generalizing their knowledge to deal with complex tasks. Over the past years, a lot of research has been done in both natural language processing (NLP) and computer vision (CV) on leveraging commonsense knowledge to improve AI models. However, no systematic comparisons of existing work...

Building Interactive Text-to-SQL Systems

Natural Language Interfaces for Databases (NLIDBs) offer a way for users to reason about data. It does not require the user to know the data structure, its relations, or familiarity with a query language like SQL. It only requires the use of Natural Language. This thesis focuses on a subset of NLIDBs, namely those with 'plain English' sentences...

Automated Writing Feedback

The rising number of students challenges the teacher’s time-consuming task to provide consistent and high-quality feedback for all students. To address the traditional education’s challenges, researchers refer to online educational tools to assist teachers. Although large writing tools (for instance, Grammarly and Microsoft Editor) assist...

Performance analysis of the state-of-the-art NLP models for predicting moral values

Moral values are instrumental in understanding people's beliefs and behaviors. Estimating such values from text would facilitate the interaction between humans and computers. To date, no comparison between NLP models for predicting moral values from text exists. This paper addresses this by comparing LSTM and more novel models such as BERT and...

Tackling the Headline Incongruity Problem using Stance Detection

The increasing amount of untrusted content on the internet is a worrisome trend. The headline of an article can be adjusted to influence a potential readers attention and click-through rate. This clickbait or sensationalism can mislead the reader as the headline does not accurately represent the information in the corresponding article body....

DilBERT^2: Humor Detection and Sentiment Analysis of Comic Texts Using Fine-Tuned BERT Models

The field of Natural Language Processing (NLP) techniques has progressed rapidly over the recent years. With new advancements in transfer learning and the creation of open-source projects like BERT, solutions and research projects emerged implementing new ideas in a variety of domains, for tasks including text classification or question...

Schema mode assessment through a conversational agent

Schema therapy is a psychotherapy for treatment of personality disorders and other psychological disorders. An important element of schema therapy is determining a patient's schema modes, a concept central to deciding the treatment approach. The objective of this work was to evaluate whether assessment of these schema modes is possible through a...

Understanding the Attackers and Victims in IoT-based DDoS attacks: A mixed methodology approach to understanding cybercrime

To protect critical services in today's society it is necessary to mitigate and prevent risks threatening the reliability of the internet. Internet-of-Things (IoT) devices are the number one attack target on the internet. The situation will become worse as there will be an expected 40 billion IoT devices in 2025. IoT bot activity represented 78%...

Pumping when the wind blows: Demand response in the Dutch delta

This thesis investigates the potential of a large pumping station in IJmuiden, the Nether-lands, for participating in Demand Response. Due to climate change, renewable energy is onthe rise. The intermittency of energy, together with its unpredictable supply, are a big hurdlefor the energy transition. Two methods are promising solutions to this...

Optimal Control for Race Car Minimum Time Maneuvering

Minimizing the time needed to travel a prescribed distance is the main development goal in motorsports. In racing car development, simulations are used to predict the effect of design parameter changes on vehicle performance. If approached as an optimal trajectory planning problem, a maneuver simulation can be used to determine not only the...