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2 resources

  • Ziwei Ji, Nayeon Lee, Rita Frieske
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    Mar 3rd, 2023
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    journalArticle
    Ziwei Ji, Nayeon Lee, Rita Frieske
    Mar 3rd, 2023

    Natural Language Generation (NLG) has improved exponentially in recent years thanks to the development of sequence-to-sequence deep learning technologies such as Transformer-based language models. This advancement has led to more fluent and coherent NLG, leading to improved development in downstream tasks such as ve summarization, dialogue generation, and data-to-text generation. However, it is also apparent that deep learning based generation is prone to hallucinate unintended text, which...

  • Yejin Bang, Samuel Cahyawijaya, Nayeon L...
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    Feb 28th, 2023
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    preprint
    Yejin Bang, Samuel Cahyawijaya, Nayeon L...
    Feb 28th, 2023

    This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of ChatGPT using 23 data sets covering 8 different common NLP application tasks. We evaluate the multitask, multilingual and multi-modal aspects of ChatGPT based on these data sets and a newly designed multimodal dataset. We find that ChatGPT outperforms LLMs with zero-shot learning on most tasks and even outperforms...

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