SubmissionNumber#=%=#130
FinalPaperTitle#=%=#BITS Pilani at SemEval-2024 Task 1: Using text-embedding-3-large and LaBSE embeddings for Semantic Textual Relatedness
ShortPaperTitle#=%=#
NumberOfPages#=%=#4
CopyrightSigned#=%=#Dilip Venkatesh
JobTitle#==#
Organization#==#
Abstract#==#Semantic Relatedness of a pair of text (sentences or words) is the degree to which their
meanings are close. The Track A of the Semantic Textual Relatedness shared task aims
to find the semantic relatedness for the English language along with multiple other low
resource languages with the use of pretrained
language models. We proposes a system to
find the Spearman coefficient of a textual pair
using pretrained embedding models like textembedding-3-large and LaBSE.
Author{1}{Firstname}#=%=#Dilip
Author{1}{Lastname}#=%=#Venkatesh
Author{1}{Username}#=%=#dipsivenkatesh
Author{1}{Email}#=%=#dipsivenkatesh@gmail.com
Author{1}{Affiliation}#=%=#BITS Pilani
Author{2}{Firstname}#=%=#Sundaresan
Author{2}{Lastname}#=%=#Raman
Author{2}{Email}#=%=#sundaresan.raman@pilani.bits-pilani.ac.in
Author{2}{Affiliation}#=%=#BITS Pilani

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