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Abstract Dialogue summarization, an essential component of intelligent dialogue systems, holds significant importance. While end-to-end summarization models exhibit robust performance, their success is contingent upon access to adequately sized annotated datasets. This requirement creates significant acquisition costs, particularly for summarizing dialogues.
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