# 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?