document

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

Afriat, Eliott (author)

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...

bachelor thesis 2023

document

Natural Language Processing for systems engineering: Automatic generation of Systems Modelling Language diagrams

Zhong, Shaohong (author), Scarinci, Andrea (author), Cicirello, A. (author)

The design of complex engineering systems is an often long and articulated process that highly relies on engineers’ expertise and professional judgment. As such, the typical pitfalls of activities involving the human factor often manifest themselves in terms of lack of completeness or exhaustiveness of the analysis, inconsistencies across...

journal article 2023

document

Deterministic bibliometric disambiguation challenges in company names

Belz, Andrea (author), Graddy-Reed, Alexandra (author), Shweta, F. N.U. (author), Giga, A. (author), Murali, Shivesh Meenakshi (author)

Peer-reviewed publications and patents serve as important signatures of knowledge generation, and therefore the authors and their organizations can represent agents of intellectual transformation. Accurate tracking of these players enables scholars to follow knowledge evolution. However, while author name disambiguation has been discussed...

conference paper 2023

document

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

Chen, Dina (author)

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...

master thesis 2022

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

Jonnalagadda, Aravind (author)

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...

master thesis 2022

document

LoveBERT: Leveraging Language Models to Improve Matchmaking at Breeze

Jongerius, Ricardo (author)

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...

master thesis 2022

document

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

Kirchner, Joris (author)

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)...

bachelor thesis 2022

document

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

Kuiper, Adrian (author)

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...

bachelor thesis 2022

document

To what degree can we use NLP to mine current and trending topics with respect to well-being?

Manglani, Neel (author)

The increase in global internet users brings forth a vast amount of social media users and therefore opinions that are shared online. A subset of those users, adolescents, seem to develop some sort of addiction towards social media, which could lead to low life satisfaction. This paper tries to extract trending topics and their relation to well...

bachelor thesis 2022

document

Building Interactive Text-to-SQL Systems

Koops, Reinier (author)

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...

master thesis 2022

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Patentopia: A multi-stage patent extraction platform with disambiguation for certain semantic challenges

Belz, Andrea (author), Graddy-Reed, Alexandra (author), Shweta, FNU (author), Giga, A. (author), Murali, Shivesh Meenakshi (author)

Bibliographic name disambiguation is an major semantic challenge, but critical to social sciences studies of important intellectual assets. Here we contribute to innovation research in several ways. We show a significant synonym problem in author names and discuss how a pre-processing heuristic step standardizing name variants helps, but...

conference paper 2022

document

SuMe: A Dataset Towards Summarizing Biomedical Mechanisms

Bastan, Mohaddeseh (author), Shankar, N. (author), Surdeanu, Mihai (author), Balasubramanian, Niranjan (author)

Can language models read biomedical texts and explain the biomedical mechanisms discussed? In this work we introduce a biomedical mechanism summarization task. Biomedical studies often investigate the mechanisms behind how one entity (e.g., a protein or a chemical) affects another in a biological context. The abstracts of these publications...

conference paper 2022

document

What values should an agent align with?: An empirical comparison of general and context-specific values

Liscio, E. (author), van der Meer, M.T. (author), Cavalcante Siebert, L. (author), Jonker, C.M. (author), Murukannaiah, P.K. (author)

The pursuit of values drives human behavior and promotes cooperation. Existing research is focused on general values (e.g., Schwartz) that transcend contexts. However, context-specific values are necessary to (1) understand human decisions, and (2) engineer intelligent agents that can elicit and align with human values. We propose Axies, a...

journal article 2022

document

Social foresights on Covid-19 futures: developing a NLP tool for Strategic Design Research

Simonse, LWL (author)

Future sense-making is the social activity by which people give meaning to their collective experiences in crisis situations such as the outbreak of Covid-19. Enacted in conversations and narratives, sense-making is a largely cognitive activity of framing experienced situations as meaningful. It is a collaborative process of creating shared...

conference paper 2022

document

Automated Writing Feedback

van der Laan, Paul (author)

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...

master thesis 2021

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

Geadău, Andrei (author)

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...

bachelor thesis 2021

document

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

Garbowicz, Krzysztof (author)

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...

bachelor thesis 2021

document

Tackling the Headline Incongruity Problem using Stance Detection

Mariën, Simon (author)

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....

bachelor thesis 2021

document

Schema mode assessment through a conversational agent

Allaart, David (author)

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...

master thesis 2021

document

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

Su, Kevin (author)

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%...

master thesis 2021