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Found 2 papers, 1 papers with code
Annotating and Detecting Fine-grained Factual Errors for Dialogue Summarization
A series of datasets and models have been proposed for summaries generated for well-formatted documents such as news articles.
Findings on Conversation Disentanglement
Conversation disentanglement, the task to identify separate threads in conversations, is an important pre-processing step in multi-party conversational NLP applications such as conversational question answering and conversation summarization.
Conversational Question Answering
Conversation Disentanglement
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