Papers by Ewa Kijak
PPL-MCTS: Constrained Textual Generation Through Discriminator-Guided MCTS Decoding (2022.naacl-main)
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| Challenge: | Large language models (LM) based on transformers generate plausible long texts . a discriminator-guided approach allows to apply constraints more finely and dynamically. |
| Approach: | They propose to use a discriminator-guided approach to generate constrained texts without fine-tuning the LM. |
| Outcome: | The proposed method is easier and cheaper to train than fine-tuning the LM. |
Generating Artificial Texts as Substitution or Complement of Training Data (2022.lrec-1)
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| Challenge: | Existing approaches to generate text for supervised learning tasks use transformers to generate learning data. |
| Approach: | They propose to use transformers to generate supervised learning data for supervised machine learning tasks and propose to train a neural language model trained on the original training texts. |
| Outcome: | The proposed models can be used in a certain extend but require pre-processing to significantly improve performance. |