Can AI Write Classical Chinese Poetry like Humans? An Empirical Study Inspired by Turing Test
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866914636863897600 |
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| author | Deng, Zekun Yang, Hao Wang, Jun |
| author_facet | Deng, Zekun Yang, Hao Wang, Jun |
| contents | Some argue that the essence of humanity, such as creativity and sentiment, can never be mimicked by machines. This paper casts doubt on this belief by studying a vital question: Can AI compose poetry as well as humans? To answer the question, we propose ProFTAP, a novel evaluation framework inspired by Turing test to assess AI's poetry writing capability. We apply it on current large language models (LLMs) and find that recent LLMs do indeed possess the ability to write classical Chinese poems nearly indistinguishable from those of humans. We also reveal that various open-source LLMs can outperform GPT-4 on this task. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_04952 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Can AI Write Classical Chinese Poetry like Humans? An Empirical Study Inspired by Turing Test Deng, Zekun Yang, Hao Wang, Jun Computation and Language Some argue that the essence of humanity, such as creativity and sentiment, can never be mimicked by machines. This paper casts doubt on this belief by studying a vital question: Can AI compose poetry as well as humans? To answer the question, we propose ProFTAP, a novel evaluation framework inspired by Turing test to assess AI's poetry writing capability. We apply it on current large language models (LLMs) and find that recent LLMs do indeed possess the ability to write classical Chinese poems nearly indistinguishable from those of humans. We also reveal that various open-source LLMs can outperform GPT-4 on this task. |
| title | Can AI Write Classical Chinese Poetry like Humans? An Empirical Study Inspired by Turing Test |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2401.04952 |