CompoundPiece: Evaluating and Improving Decompounding Performance of Language Models (2023.emnlp-main)
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| Challenge: | Currently, there is no dataset containing compound and non-compound words across languages . however, current LLMs perform poorly on words tokenized unfavorably by subword tokenization. |
| Approach: | They propose to use a Wiktionary dataset to evaluate large language models on decompounding . they find that current LLMs perform poorly on words tokenized unfavorably . |
| Outcome: | The proposed model outperforms the best unsupervised models by 13.9% accuracy on average. |
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