Papers with dialogue comprehension tasks

2 papers
STRUDEL: Structured Dialogue Summarization for Dialogue Comprehension (2022.emnlp-main)

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Challenge: Abstractive dialogue summarization is an important standalone task in natural language processing, but no previous work has explored whether it can be used to boost an NLP system's performance on other important dialogue comprehension tasks.
Approach: They propose a novel type of dialogue summarization task that decomposes and imitates the hierarchical, systematic and structured mental process that human beings usually go through when understanding and analyzing dialogues.
Outcome: The proposed model improves the performance of transformer encoder language models on two important dialogue comprehension tasks.
Multi-Source Probing for Open-Domain Conversational Understanding (2023.emnlp-main)

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Challenge: Existing models of open-domain dialogue comprehension have limited conversational understanding and response generation.
Approach: They propose a multi-source probing method to probe dialogue comprehension abilities of open-domain dialogue models.
Outcome: The proposed method aggregates features from multiple sources to accomplish diverse task goals and conducts downstream tasks in a generative manner consistent with dialogue model pre-training to leverage model capabilities.

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