Sökning: "Large Language Model."
Visar resultat 1 - 5 av 275 uppsatser innehållade orden Large Language Model..
1. Where to Fuse
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : 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. LÄS MER
2. An In-Depth study on the Utilization of Large Language Models for Test Case Generation
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : 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. LÄS MER
3. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
Kandidat-uppsats, Lunds universitet/Fysiska institutionenSammanfattning : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. LÄS MER
4. Initial Development and Validation of Language-Based Assessments for Meaningful Change
Kandidat-uppsats, Lunds universitet/Institutionen för psykologiSammanfattning : Meaningful change has been discussed in multiple studies, with the recurring question of how it could be conceptualized and assessed to identify what determines meaningful change and where it occurs. Previous studies have conducted statistical analyses based on traditional rating scales (i.e., the PHQ-9) to assess meaningful change. LÄS MER
5. Bridging Language & Data : Optimizing Text-to-SQL Generation in Large Language Models
Master-uppsats, Linköpings universitet/Artificiell intelligens och integrerade datorsystemSammanfattning : 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. LÄS MER