All datasets / INK-USC
INK-USC/xcsr
The declared licence (mit) is classified as permissive.
- Declared licence
- mit, from the tagEvidence: README.md at f691f31
- Licence files
- No licence file at the top level of the repositoryEvidence: file list at f691f31
- Declared sources
- 2
- Access gated on Hugging Face
- No
Sources listed in the card metadata
- codahodc-byPermissiveEvidence: README.md at 4b0e0e7
- commonsense_qamitPermissiveEvidence: README.md at 94630fe
Tasks
Citation text from the card
```
# X-CSR
@inproceedings{lin-etal-2021-common,
title = "Common Sense Beyond {E}nglish: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning",
author = "Lin, Bill Yuchen and
Lee, Seyeon and
Qiao, Xiaoyang and
Ren, Xiang",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-long.102",
doi = "10.18653/v1/2021.acl-long.102",
pages = "1274--1287",
abstract = "Commonsense reasoning research has so far been limited to English. We aim to evaluate and improve popular multilingual language models (ML-LMs) to help advance commonsense reasoning (CSR) beyond English. We collect the Mickey corpus, consisting of 561k sentences in 11 different languages, which can be used for analyzing and improving ML-LMs. We propose Mickey Probe, a language-general probing task for fairly evaluating the common sense of popular ML-LMs across different languages. In addition, we also create two new datasets, X-CSQA and X-CODAH, by translating their English versions to 14 other languages, so that we can evaluate popular ML-LMs for cross-lingual commonsense reasoning. To improve the performance beyond English, we propose a simp
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dataset_licence({ "id": "INK-USC/xcsr" })
signal: "permissive"
stated_licence: "mit"
sources: 2