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# Wikitext
### Paper
Pointer Sentinel Mixture Models
https://arxiv.org/pdf/1609.07843.pdf
The WikiText language modeling dataset is a collection of over 100 million tokens
extracted from the set of verified Good and Featured articles on Wikipedia.
NOTE: This `Task` is based on WikiText-2.
Homepage: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
### Citation
```
@misc{merity2016pointer,
title={Pointer Sentinel Mixture Models},
author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},
year={2016},
eprint={1609.07843},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
### Groups and Tasks
#### Groups
* Not part of a group yet.
#### Tasks
* `wikitext`: measure perplexity on the Wikitext dataset, via rolling loglikelihoods.
### Checklist
* [x] Is the task an existing benchmark in the literature?
* [x] 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:
* [x] Is the "Main" variant of this task clearly denoted?
* [x] 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?
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