MaiNLP's Submission to SemEval-2024 Task 1: Exploring Source Language Selection Strategies for Cross-Lingual Semantic Textual Relatedness
This paper presents the MaiNLP team's system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR), focusing on the cross-lingual track. The team explores different source language selection strategies, including single-source transfer, multi-source transfer, and transfer from nearest language neighbors, to improve zero-shot cross-lingual performance on the STR task.
SemEval-2024 Task 1: Cross-lingual Semantic Textual Relatedness without Direct Supervision
This paper presents a system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR), on Track C: Cross-lingual. The task aims to detect semantic relatedness of two sentences in a given target language without access to direct supervision. The authors focus on different source language selection strategies on two different pre-trained language models: XLM-R and FURINA.
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