Searched for: subject%3A%22large%255C+language%255C+models%22
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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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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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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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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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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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Sapozhnikov, Arkadii (author), Olsthoorn, Mitchell (author), Panichella, A. (author), Kovalenko, V.V. (author), Derakhshanfar, P. (author)
Writing software tests is laborious and time-consuming. To address this, prior studies introduced various automated test-generation techniques. A well-explored research direction in this field is unit test generation, wherein artificial intelligence (AI) techniques create tests for a method/class under test. While many of these techniques have...
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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Al-Kaswan, A. (author)
Large Language Models (LLMs) are gaining popularity in the field of Natural Language Processing (NLP) due to their remarkable accuracy in various NLP tasks. LLMs designed for coding are trained on massive datasets, which enables them to learn the structure and syntax of programming languages. These datasets are scraped from the web and LLMs...
conference paper 2024
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Katzy, J.B. (author)
Large language models have become increasingly utilized in programming contexts. However, due to the recent emergence of this trend, some aspects have been overlooked. We propose a research approach that investigates the inner mechanics of transformer networks, on a neuron, layer, and output representation level, to understand whether there...
conference paper 2024
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Deljouyi, A. (author)
Automatic unit test generators, particularly search-based software testing (SBST) tools such as EvoSuite, efficiently generate unit test suites with acceptable coverage. Although this removes the burden of writing unit tests from developers, these generated tests often pose challenges in terms of comprehension for developers. In my doctoral...
conference paper 2024
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de Winter, J.C.F. (author), Driessen, T. (author), Dodou, D. (author)
Personality research has traditionally relied on questionnaires, which bring with them inherent limitations, such as response style bias. With the emergence of large language models such as ChatGPT, the question arises as to what extent these models can be used in personality research. In this study, ChatGPT (GPT-4) generated 2000 text-based...
journal article 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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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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