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  license: cc-by-4.0
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- Please find additional data files specific to each language at this GitHub repo https://github.com/jatuhurrra/LLM-for-Intent-Classification/tree/main/data
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  # Large language models (i.e., GPT-4) for Zero-shot Intent Classification in English (En), Japanese (Jp), Swahili (Sw) & Urdu (Ur)
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  This project explores the potential of deploying large language models (LLMs) such as GPT-4 for `zero-shot intent recognition`. We demonstrate that LLMs can perform intent classification through prompting. This aligns with the ongoing trend of exploiting the power of `in-context learning` in LLMs without the need for extensive fine-tuning.
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  To test our hypothesis, we introduce a dataset to explore and analyze zero-shot intent classification further, providing a valuable resource for the research community.
 
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  license: cc-by-4.0
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  # Large language models (i.e., GPT-4) for Zero-shot Intent Classification in English (En), Japanese (Jp), Swahili (Sw) & Urdu (Ur)
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+ <span style="color:blue">Please find additional data files specific to each language at this GitHub repo <a href="https://github.com/jatuhurrra/LLM-for-Intent-Classification/tree/main/data">https://github.com/jatuhurrra/LLM-for-Intent-Classification/tree/main/data</a></span>
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  This project explores the potential of deploying large language models (LLMs) such as GPT-4 for `zero-shot intent recognition`. We demonstrate that LLMs can perform intent classification through prompting. This aligns with the ongoing trend of exploiting the power of `in-context learning` in LLMs without the need for extensive fine-tuning.
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  To test our hypothesis, we introduce a dataset to explore and analyze zero-shot intent classification further, providing a valuable resource for the research community.