Searched for: subject%3A%22Language%255C+Models%22
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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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Castagnaro, Alberto (author)
Web Vulnerability Assessment and Penetration Testing (Web VAPT) is an important cybersecurity practice that thoroughly examines web applications to uncover possible vulnerabilities. These vulnerabilities represent potential security gaps that could severely compromise the web applications' integrity and functionality if exploited by malicious...
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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Vignisson, Snorri (author)
This thesis investigates the integration of Large Language Models (LLMs) within large organizations operating in low resource language (LRL) regions, with a particular focus on Íslandsbanki, one of the prominent banks in Iceland currently grappling with the adoption of LLM technology. The research aims to understand the frameworks governing LLM...
master thesis 2024
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Tabone, W. (author)
This thesis explores how automated vehicles will interact with pedestrians in the urban environment through augmented reality technology. Nine distinct AR interfaces were designed, developed, and evaluated to assess how different design elements (symbols, text, colour) and distinct mappings of the AR (on the road, on the vehicle, or head-locked)...
doctoral 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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Rainey, S. (author)
This article examines the idea of mind-reading technology by focusing on an interesting case of applying a large language model (LLM) to brain data. On the face of it, experimental results appear to show that it is possible to reconstruct mental contents directly from brain data by processing via a chatGPT-like LLM. However, the author argues...
journal article 2024
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Cambaz, Doga (author), Zhang, X. (author)
The recent emergence of LLM-based code generation models can potentially transform programming education. To pinpoint the current state of research on using LLM-based code generators to support the teaching and learning of programming, we conducted a systematic literature review of 21 papers published since 2018. The review focuses on (1) the...
conference paper 2024
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Kernan Freire, S. (author), Wang, C.W. (author), Foosherian, Mina (author), Wellsandt, Stefan (author), Ruiz-Arenas, Santiago (author), Niforatos, E. (author)
Recent advances in natural language processing enable more intelligent ways to support knowledge sharing in factories. In manufacturing, operating production lines has become increasingly knowledge-intensive, putting strain on a factory's capacity to train and support new operators. This paper introduces a Large Language Model (LLM)-based system...
journal article 2024
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Wallat, Jonas (author), Jatowt, Adam (author), Anand, A. (author)
Large language models (LLMs) have recently gained significant attention due to their unparalleled zero-shot performance on various natural language processing tasks. However, the pre-Training data utilized in LLMs is often confined to a specific corpus, resulting in inherent freshness and temporal scope limitations. Consequently, this raises...
conference paper 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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Sinha, Tishar (author)
This research introduces a novel approach for 3D object detection utilizing language models, with a particular focus on addressing the challenges that have been encountered in the autonomous vehicle domain. The primary objective revolves around addressing the constraints associated with object detection models that rely heavily on labeled data...
master thesis 2023
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van Wijngaarden, Matthijs (author)
Large chemical reaction databases often suffer from incompleteness, such as missing molecules or stoichiometric information. Concurrently, numerous computational models are being developed in predictive chemistry that rely on reaction databases and would hugely benefit from complete reaction equations. Also, research in sustainable chemistry...
master thesis 2023
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Timmerman, Gerben (author)
This thesis offers a comprehensive exploration of log-based anomaly detection within the domain of cybersecurity incident response. The research describes a different approach and explores relevant log features for language model training, experimentation with different language models and training methodologies, and the investigation of the...
master thesis 2023
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Klop, Pepijn (author)
This research introduces a Language Model Augmented Program Synthesis (LMAPS) workflow to enhance traditional Programming by Example (PBE). PBE is a method to automatically generate a program that satisfies a specification that consists of a set of input-output examples. These program specifications are often defined by a few examples, which can...
master thesis 2023
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Sándor, Kristóf (author)
Large Language Models (LLM) have brought significant performance increase on many Natural Language Processing tasks. However LLMs have not been tested for meeting summarization. This research paper examines the effectiveness of the gpt-3.5-turbo model on the meeting summarization domain. However due to input length limitations, it cannot be...
bachelor 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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de Weerd, Daniël (author)
This paper presents a novel approach to detect agreement and disagreement moments between participants in meeting transcripts without relying on labeled data. We propose a model in which disagreement detection is defined as the process of first identifying argumentative theses relevant to a given corpus of text and then classifying all phrases...
bachelor thesis 2023
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