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OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experience

This repository is for the paper OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experience

In this work, we propose a new task, Open-Book TOD (OB-TOD), which combines TOD with QA and expands the external knowledge sources to include both explicit sources (e.g., the web) and implicit sources (e.g., pre-trained language models). We create a new dataset OB-MultiWOZ, where we enrich TOD sessions with QA-like information-seeking experience grounded on external knowledge. We propose a unified model OPERA (Open-book End-to-end Task-oriented Dialog) which can appropriately access explicit and implicit external knowledge to tackle the OB-TOD task. Experimental results show that OPERA outperforms closed-book baselines, highlighting the value of both types of knowledge

This repository is based on hugginface transformer and OpenAI GPT-3. Some scripts and dataset are adapted from DSTC9.

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