MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents (2021.emnlp-main)
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| Challenge: | Existing work treats document-grounded dialogue modeling as a machine reading comprehension task based on a single document or passage. |
| Approach: | They propose a task and dataset for modeling goal-oriented dialogues grounded in multiple documents. |
| Outcome: | The proposed task and dataset address realistic scenarios where goal-oriented dialogues involve multiple topics and hence are grounded on different documents. |
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| Challenge: | doc2dial dataset is a goal-oriented document-grounded dialogue model . it is based on how the authors compose documents for guiding end users . |
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| Challenge: | Using a multi-task learning framework, we train a universal incremental dialogue processing model with four tasks of disfluency detection, language modelling, part-of-speech tagging and utterance segmentation in a simple deep recurrent setting. |
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