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# Wikitext |
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### Paper |
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Pointer Sentinel Mixture Models |
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https://arxiv.org/pdf/1609.07843.pdf |
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The WikiText language modeling dataset is a collection of over 100 million tokens |
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extracted from the set of verified Good and Featured articles on Wikipedia. |
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NOTE: This `Task` is based on WikiText-2. |
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Homepage: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ |
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### Citation |
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``` |
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@misc{merity2016pointer, |
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title={Pointer Sentinel Mixture Models}, |
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author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher}, |
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year={2016}, |
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eprint={1609.07843}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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### Groups and Tasks |
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#### Groups |
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* Not part of a group yet. |
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#### Tasks |
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* `wikitext`: measure perplexity on the Wikitext dataset, via rolling loglikelihoods. |
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### Checklist |
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* [x] Is the task an existing benchmark in the literature? |
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* [x] Have you referenced the original paper that introduced the task? |
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* [ ] 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? |
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If other tasks on this dataset are already supported: |
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* [x] Is the "Main" variant of this task clearly denoted? |
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* [x] Have you provided a short sentence in a README on what each new variant adds / evaluates? |
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* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? |
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