Papers by Jonas Belouadi
ByGPT5: End-to-End Style-conditioned Poetry Generation with Token-free Language Models (2023.acl-long)
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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. |
| Approach: | They propose to train end-to-end poetry generation conditioned on styles such as rhyme, meter, and alliteration . they pre-train ByGPT5, a new token-free decoder-only language model, and fine-tune it on a custom corpus of English and German quatrains . |
| Outcome: | The proposed model outperforms other models on a large custom corpus of English and German quatrains while being more parameter efficient and performing favorably compared to humans. |
UScore: An Effective Approach to Fully Unsupervised Evaluation Metrics for Machine Translation (2023.eacl-main)
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| Challenge: | supervised evaluation metrics are not available for machine translation, despite their wide dissemination. |
| Approach: | They develop fully unsupervised evaluation metrics that leverage parallel data and evaluation metric induction. |
| Outcome: | The proposed metrics beat supervised competitors on 4 out of 5 evaluation datasets. |
Reproducibility Issues for BERT-based Evaluation Metrics (2022.emnlp-main)
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| Challenge: | Reproducibility is of utmost concern in machine learning and natural language processing . lexical-overlap metrics are still the dominant metric in natural language generation . |
| Approach: | They ask whether results and claims from four recent BERT-based evaluation metrics can be reproduced. |
| Outcome: | The proposed metrics outperform the dominant metric, BLEU, and show that they can be reproduced. |