Essays about: "language input"
Showing result 1 - 5 of 279 essays containing the words language input.
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1. Where to Fuse
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis investigates fusion techniques in multimodal transformer models, focusing on enhancing the capabilities of large language models in understanding not just text, but also other modalities like images, audio, and sensor data. The study compares late fusion (concatenating modality tokens after separate encoding) and early fusion (concatenating before encoding) techniques, examining their respective advantages and disadvantages. READ MORE
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2. An In-Depth study on the Utilization of Large Language Models for Test Case Generation
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : This study investigates the utilization of Large Language Models for Test Case Generation. The study uses the Large Language model and Embedding model provided by Llama, specifically Llama2 of size 7B, to generate test cases given a defined input. READ MORE
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3. Incidental Vocabulary Learning in EFL Through Reading, Listening, and Watching
University essay fromAbstract : Incidental vocabulary learning is a form of acquiring new words without having a specific intention in the acquisition, and it can occur in or out of the educational frame (Hatami, 2017). In the digital age, incidental vocabulary acquisition is increased as learners encounter and assimilate new words through different online platforms and technological tools. READ MORE
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4. Bridging Language & Data : Optimizing Text-to-SQL Generation in Large Language Models
University essay from Linköpings universitet/Artificiell intelligens och integrerade datorsystemAbstract : This thesis explores text-to-SQL generation using Large Language Models within a financial context, aiming to assess the efficacy of current benchmarks and techniques. The central investigation revolves around the accuracy of the BIRD-Bench benchmark and the applicability of text-to-SQL models in real-world scenarios. READ MORE
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5. Approximating Reasoning with Transformer Language Models
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : We conduct experiments with BART, a generative language-model architecture, to investigate its capabilities for approximating reasoning by learning from data. For this we use the SimpleLogic dataset, a dataset of satisfiability problems in propositional logic originally created by Zhang et al. (2022). READ MORE
