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MuTual

Paper

Title: MuTual: A Dataset for Multi-Turn Dialogue Reasoning

Abstract: https://www.aclweb.org/anthology/2020.acl-main.130/

MuTual is a retrieval-based dataset for multi-turn dialogue reasoning, which is modified from Chinese high school English listening comprehension test data.

Homepage: https://github.com/Nealcly/MuTual

Citation

@inproceedings{mutual,
    title = "MuTual: A Dataset for Multi-Turn Dialogue Reasoning",
    author = "Cui, Leyang  and Wu, Yu and Liu, Shujie and Zhang, Yue and Zhou, Ming" ,
    booktitle = "Proceedings of the 58th Conference of the Association for Computational Linguistics",
    year = "2020",
    publisher = "Association for Computational Linguistics",
}

Groups and Tasks

Groups

  • Not part of a group yet.

Tasks

  • mutual
  • mutual_plus

Checklist

For adding novel benchmarks/datasets to the library:

  • Is the task an existing benchmark in the literature?
    • Have you referenced the original paper that introduced the task?
    • If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?

If other tasks on this dataset are already supported:

  • Is the "Main" variant of this task clearly denoted?
  • Have you provided a short sentence in a README on what each new variant adds / evaluates?
  • Have you noted which, if any, published evaluation setups are matched by this variant?