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Snoeij, Corné (author)This research explores the use of Artificial Intelligence (AI), specifically Large Language Models (LLMs), into the operationalization of Government Technology (GovTech) benchmarks to increase their utility for policymakers. Research and practice consistently highlight persistent challenges in GovTech benchmarking, such as resource-intensive...master thesis 2024
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Uno, Taichi (author)Understanding how users retrospectively evaluate their interactions with adaptive intelligent systems is crucial to improving their behaviours during interactions. Prior work has shown the potential to predict retrospective evaluations based on different real-time aspects of conversations, such as verbal cues and non-verbal behaviours. However,...master thesis 2024
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Blagoev, Nikolay (author)Motivated by the emergence of Large Language Models (LLMs) and the importance of democratizing their training, we propose Go With The Flow, the first practical decentralized training framework for LLMs. Differently from existing distributed and federated training frameworks, Go With The Flow enables the collaborative training of an LLM on a set...master thesis 2024
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Xu, ZIHAO (author)Large Language Models (LLMs) have emerged as pivotal in content generation, offering profound societal impacts. Previous research has highlighted their propensity to generate content that breaches societal norms. Misuse of LLMs poses significant ethical concerns, including misinformation spread, social unrest, and political manipulation. To...master thesis 2024
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Collé, Baptiste (author)The emergence of Language Language Models (LLMs)-based agents represents a significant advancement in artificial intelligence (AI), offering new possibilities for complex problem-solving and interaction within a virtual environment. Our work is based on the Voyager paper [1], which is a state-of-the-art LLM-based agent for Minecraft. However,...master thesis 2024
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O'Dwyer Wha Binda, Jahson (author)With the increasing popularity of Large Language Models (LLMs), fine-tuning them has become increasingly computationally expensive. Parameter Efficient Fine-Tuning (PEFT) methods like LoRA and Adapters, introduced by Microsoft and Google, respectively, aim to reduce the number of trainable parameters, with the current state-of-the-art combining...master thesis 2024
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Kooij, Matthew (author)Generative AI is expected to have a significant impact on how business is done, especially for knowledge-intensive domains. Professional usage amongst knowledge workers is already widespread and many of them believe that LLM use for work will make them more efficient, help them generate ideas, and improve the quality of their work. Yet, the...master thesis 2024
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Verduijn, Luc (author)In the past year, generative AI has made significant leaps, making it more accessible, helpful, and known to the broader public. This technology promises to change how we work, automating repetitive tasks, generating content, and assisting in problem-solving scenarios easier. This research explores how implementing this new technology will...master thesis 2024
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Chen, Ivo (author)Large language models (LMs) are increasingly used in critical tasks, making it important that these models can be trusted. The confidence an LM assigns to its prediction is often used to indicate how much trust can be placed in that prediction. However, a high confidence can be incorrectly trusted if it turns out to be incorrect, also known as a...master thesis 2024
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Nandkumar, CHANDRAN (author)This thesis presents the design and evaluation of a comprehensive system for developing voice-based interfaces to support users in supermarkets. These interfaces enable customers to convey their needs across both generic and specific queries. While current state-of-the-art systems like GPTs by OpenAI are easily accessible and adaptable,...master thesis 2024
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Gupta, Dibyendu (author)The growth of academic publications, heterogeneity of datasets and the absence of a globally accepted organization identifier introduce the challenge of affiliation disambiguation in bibliographic databases. In this paper, we create a baseline using the currently implemented algorithm for author affiliation linkage in Alexandria3k by comparing...bachelor thesis 2024
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van Lieshout, Jelle (author)Author name disambiguation, otherwise described as (publication) record linking, is a problem that has had considerable research dedicated to its solv- ing. Author attributions, calculating research met- rics and conducting literature reviews are amongst processes that experience increased difficulty due to ambiguous author names. In this study,...bachelor thesis 2024
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Klenk, M.B.O.T. (author)Generative AI enables automated, effective manipulation at scale. Despite the growing general ethical discussion around generative AI, the specific manipulation risks remain inadequately investigated. This article outlines essential inquiries encompassing conceptual, empirical, and design dimensions of manipulation, pivotal for comprehending...journal article 2024
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Neague, P.M. (author), Gregoriadis, M.I. (author), Pouwelse, J.A. (author)This study introduces De-DSI, a novel framework that fuses large language models (LLMs) with genuine decentralization for information retrieval, particularly employing the differentiable search index (DSI) concept in a decentralized setting. Focused on efficiently connecting novel user queries with document identifiers without direct document...conference paper 2024
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van Leeuwen, Sander (author)Language is an intuitive and effective way for humans to communicate. Large Language Models (LLMs) can interpret and respond well to language. However, their use in deep reinforcement learning is limited as they are sample inefficient. State-of-the-art deep reinforcement learning algorithms are more sample efficient but cannot understand...master thesis 2023
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Domhof, Jan (author)Meetings are the keystone of a good company. They allow for quick decision making, multiple-perspective problem solving and effective communication. However, most employees and managers have a negative view on the efficiency and quality of their meetings. High quality meetings where every participant feels equally heard and respected is crucial...bachelor thesis 2023
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Keeler, Miranda (author)We present an investigation into the relationship between the average depth of the first correct prediction and the performance of CodeGen. This was done on a dataset comprised of code files comprised of C++, Go, Java, Julia, Kotlin, and Python. The analysis involved investigating the model's predictions at different layers using a Tuned Lens,...bachelor thesis 2023
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Kuo, Nadine (author)The development of contemporary source code auto-completion tools have significantly boosted productivity and efficiency of developers. In 2021, the GPT-2-based Transformer CodeGPT was developed to support code completion and text-to-code generation. Similarly to most code models however, CodeGPT was trained on a limited set of widely-used...bachelor thesis 2023
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Malmsten, Emil (author)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,...bachelor thesis 2023
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Mulder, Rick (author)Using AI to support programming has recently gained a lot of popularity. Researchers have been developing tools to support programming activities using GPT models such as ChatGPT and Codex In this paper, we present the most common pro-gramming activities that these models can support. We show that they have a varying range of success<br/>across...bachelor thesis 2023
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