Papers by Mengliang Rao

1 papers
DialogQAE: N-to-N Question Answer Pair Extraction from Customer Service Chatlog (2023.findings-emnlp)

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Challenge: Existing work on question-answer extraction fails to integrate incomplete utterances from dialog context for composite QA retrieval.
Approach: They propose a task where questions and corresponding answers might be separated across different utterances.
Outcome: The proposed methods perform well on 5 customer service datasets and set a benchmark for N-to-N DialogQAE with utterance and session level evaluation metrics.

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