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---
task_categories:
- text-classification
- multiple-choice
language:
- en
tags:
- explanation
---
https://github.com/wangcunxiang/Sen-Making-and-Explanation
```
@inproceedings{wang-etal-2019-make,
title = "Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation",
author = "Wang, Cunxiang and
Liang, Shuailong and
Zhang, Yue and
Li, Xiaonan and
Gao, Tian",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/P19-1393",
pages = "4020--4026",
abstract = "Introducing common sense to natural language understanding systems has received increasing research attention. It remains a fundamental question on how to evaluate whether a system has the sense-making capability. Existing benchmarks measure common sense knowledge indirectly or without reasoning. In this paper, we release a benchmark to directly test whether a system can differentiate natural language statements that make sense from those that do not make sense. In addition, a system is asked to identify the most crucial reason why a statement does not make sense. We evaluate models trained over large-scale language modeling tasks as well as human performance, showing that there are different challenges for system sense-making.",
}
``` |