Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset

@article{Liu2022InformationEA,
  title={Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset},
  author={Hong Liu and Hao Peng and Zhijian Ou and Juan-Zi Li and Yi Huang and Junlan Feng},
  journal={ArXiv},
  year={2022},
  volume={abs/2209.13464}
}
Recently, there have merged a class of task-oriented dialogue (TOD) datasets collected through Wizard-of-Oz simulated games. How-ever, the Wizard-of-Oz data are in fact simulated data and thus are fundamentally different from real-life conversations, which are more noisy and casual. Recently, the SereTOD challenge is organized and releases the MobileCS dataset, which consists of real-world dialog transcripts between real users and customer-service staffs from China Mobile. Based on the MobileCS… 

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