Papers by Huan Yee Koh

2 papers
How Far are We from Robust Long Abstractive Summarization? (2022.emnlp-main)

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Challenge: Abstractive summarization has made tremendous progress in recent years . however, even under a short document setting, abstractive models often generate summaries that are repetitive, ungrammatical, and factually inconsistent with the source.
Approach: They perform fine-grained human annotations to evaluate long document abstractive summarization systems and develop factual consistency metrics.
Outcome: The proposed model can generate more relevant summaries but not factual ones.
Leveraging Information Bottleneck for Scientific Document Summarization (2021.findings-emnlp)

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Challenge: Existing methods to extract salient sentences from document are unsupervised and rely on graph-based methods for sentence ranking.
Approach: They propose an unsupervised extractive approach to document level summarization based on the Information Bottleneck principle.
Outcome: The proposed framework can be extended to a multi-view framework by different signals.

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