How do you deal with texts that does not fit in the language model?

google-research-datasets / xsum_hallucination_annotations

Faithfulness and factuality annotations of XSum summaries from our paper "On Faithfulness and Factuality in Abstractive Summarization" (https://www.aclweb.org/anthology/2020.acl-main.173.pdf).

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How do you deal with texts that does not fit in the language model? #10

Open felipemaiapolo opened 1 year ago

felipemaiapolo commented 1 year ago

Thank you for making the data public!

In your paper, how do you deal with source texts that do not fit in the language model (to generate BERTScore, for example)?

Thank you, Felipe