Papers with topic classification tasks

2 papers
Multi-Source Text Classification for Multilingual Sentence Encoder with Machine Translation (2024.naacl-srw)

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Challenge: Pre-trained multilingual sentence encoders suffer from performance degradation for non-English languages.
Approach: They propose a method of machine translating a source sentence into English and then inputting it together with the source sentence in a multi-source manner.
Outcome: The proposed method improves the performance of pre-trained multilingual sentence encoders in Japanese on sentiment analysis and topic classification tasks.
LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons (2024.findings-emnlp)

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Challenge: Existing word-to-word translations from labeled task data in low-resource languages have limited lexical overlap with task data.
Approach: They propose a method that generates low-resource-language classification task data at scale using bilingual lexicons.
Outcome: The proposed method improves on 17 low-resource languages with bilingual lexicons compared with existing models on sentiment analysis and topic classification tasks.

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