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Status: Unchecked ×Keyword: code-switching ×Clear all

2 claims from 1 paper

1. Computer Science › Sentiment Analysis and Opinion Mining

   Use of prompt-based learning for code-mixed and code-switched text classification

   Udawatta, Udayangana, Gamage, Shekhar and Ranathunga · World Wide Web · 2024

   The paper explores prompt-based learning for classifying code-mixed and code-switched text, analyses the effect of script, and proposes Dynamic+AdapterPrompt, which outperforms fine-tuning baselines and basic prompting.

   Unchecked2 claims
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   1. UncheckedHow well code-mixed and code-switched text is classified depends significantly on whether several scripts are used and how intensely languages are mixed.“Our study reveals that the performance in classifying CMCS text is significantly influenced by the inclusion of multiple scripts and the intensity of code-mixing.”
   2. UncheckedA new prompt-based method, Dynamic+AdapterPrompt, outperformed fine-tuning baselines and basic prompting on code-mixed text tasks in three language pairs.“Our experiments on Sinhala-English, Kannada-English, and Hindi-English datasets for sentiment classification, hate-speech detection, and humour detection tasks show that our method outperforms strong fine-tuning baselines and basic prompting strategies.”