Papers by Jeewoo Sul

2 papers
Balancing Lexical and Semantic Quality in Abstractive Summarization (2023.acl-short)

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Challenge: Existing methods to reduce exposure bias in sequence-to-sequence models are underexplored.
Approach: They propose a method to re-rank sequence-to-sequence neural models to reduce exposure bias.
Outcome: The proposed method achieves an 89.67 BERTScore on the CNN/DailyMail and XSum datasets.
Is Prompt Transfer Always Effective? An Empirical Study of Prompt Transfer for Question Answering (2024.naacl-short)

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Challenge: Prompt tuning is an efficient method for initializing pre-trained models . but initialization of prompts is sensitive when the model size is small .
Approach: They propose a method to measure catastrophic forgetting by analyzing prompts for the first time . they characterize a question answering task based on answer format and prompt initialization .
Outcome: The proposed approach can help deepen understanding of prompt tuning.

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