Papers by Jey Lau
Summarizing Multiple Documents with Conversational Structure for Meta-Review Generation (2023.findings-emnlp)
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| Challenge: | Existing models for abstractive text summarization do not provide explicit interdocument relationships among source documents. |
| Approach: | They propose a model that uses sparse attention based on the conversational structure and a multi-task training objective that predicts metadata features. |
| Outcome: | The proposed model outperforms baseline models in terms of evaluation metrics but struggle to handle conflicts in source documents. |
Unsupervised Lexical Simplification with Context Augmentation (2023.findings-emnlp)
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| Challenge: | Existing unsupervised lexical simplification methods only use monolingual data and pre-trained models. |
| Approach: | They propose an unsupervised method that generates substitutes based on monolingual data and pre-trained language models. |
| Outcome: | The proposed method outperforms existing models on the TSAR-2022 task in English, Portuguese, and Spanish. |
DeltaScore: Fine-Grained Story Evaluation with Perturbations (2023.findings-emnlp)
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| Challenge: | Existing evaluation metrics for stories are limited in assessing intricate aspects of storytelling, such as fluency and interestingness. |
| Approach: | They propose a novel method that uses perturbation techniques to evaluate story aspects . they compare fluency, coherence, relatedness, logicality, interestingness and interestingness to existing metrics . |
| Outcome: | The proposed method shows that one specific perturbation is highly effective in capturing multiple aspects. |