The content discusses the challenges of emotion classification in text and the domain-specific nature of emotion categories. It highlights the importance of zero-shot classifications and the research gap regarding prompting language models for non-English texts. The experiments with natural language inference-based models show consistent better performance using English prompts even with data in a different language. The paper addresses questions about transferring prompts for zero-shot emotion classification across languages, analyzing prompt types' stability, and consistency across different NLI models.
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arxiv.org
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