Papers by Liam van der Poel

1 papers
Mutual Information Alleviates Hallucinations in Abstractive Summarization (2022.emnlp-main)

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Challenge: Abstractive summarization models exhibit the tendency to hallucinate, i.e., output content not supported by the source document.
Approach: They propose a decoding strategy that optimizes for pointwise mutual information of source and target tokens when models exhibit uncertainty.
Outcome: The proposed method decreases the probability of hallucinated tokens while maintaining the Rouge and BERT-S scores of top-performing decoding strategies.

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