Investigating Syntactic Enhancements in LLMs with Graph Convolutional Networks for Natural Language Inference
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ACRIUDF77" target="_blank" >RIV/00216208:11320/23:CRIUDF77 - isvavai.cz</a>
Result on the web
<a href="https://studenttheses.uu.nl/handle/20.500.12932/44529" target="_blank" >https://studenttheses.uu.nl/handle/20.500.12932/44529</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Investigating Syntactic Enhancements in LLMs with Graph Convolutional Networks for Natural Language Inference
Original language description
"This Master’s Thesis presents an exploration of incorporating syntax treesninto pre-trained Large Language Models (LLMs) for the task of Natural Lan-nguage Inference (NLI)."
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů