Help me write a Poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing (2022.emnlp-main)
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| Challenge: | Recent work in training large language models to follow natural language instructions has opened up exciting opportunities for natural language interface design. |
| Approach: | They propose to train large language models to follow natural language instructions and to test whether LLMs improve the quality of the generated content. |
| Outcome: | The proposed system is competitive to publicly available LLMs trained on instructions and can satisfy unseen compositional instructions. |
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Andrei Popescu-Belis, Àlex Atrio, Valentin Minder, Aris Xanthos, Gabriel Luthier, Simon Mattei, Antonio Rodriguez
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| Challenge: | In recent years, successful approaches have emerged to accurately model various aspects of natural language. |
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| Challenge: | Existing models for automatic poetry generation are based on maximum likelihood estimation (MLE) MLE-based models tend to remember common patterns of the poetry corpus, which results in loss-evaluation mismatch. |
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| Challenge: | Despite promising results, our analysis reveals persistent issues in the translations generated by ChatGPT that warrant attention. |
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Guo Zhipeng, Xiaoyuan Yi, Maosong Sun, Wenhao Li, Cheng Yang, Jiannan Liang, Huimin Chen, Yuhui Zhang, Ruoyu Li
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| Challenge: | End-to-end models learn to complete a task by directly learning all steps, without intermediary algorithms such as hand-crafted rules or post-processing. |
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Sonnet or Not, Bot? Poetry Evaluation for Large Models and Datasets (2024.findings-emnlp)
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| Challenge: | a task evaluates how well LLMs recognize poetry, but performance varies by poetic form . performance varying by poetic forms; models struggle to identify unfixed poetic forms . |
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