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@@ -81,33 +81,44 @@ This variant of the dataset is intended for training Chain-of-Thought reasoning
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  This dataset presents in-context scenarios where models can outsource the computations in the reasoning chain to a calculator.
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  ## Attributes:
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- - `id`: id of the example
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- - `question`: problem description in English
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- - `chain`: series of simple operations (derived from `expression`) that lead to the solution
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- - `result`: the solution for x as a number or fraction (string)
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- - `result_float`: same as `result` but converted to a float
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- - `result_unit`: the units of the result
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- - `grade`: an estimate of the school grade in which the problem would be practiced
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- - `source_question`: the source from which the example originates
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- Attributes `id`, `question`, `chain`, and `result` are present in all datasets in the [Calc-X collection](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483).
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- ## Data splits
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- The dataset does not contain data splits. We consider the whole dataset as a testing benchmark.
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- ## Licence
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- CC BY-NC 4.0, consistent with the original source dataset linked above.
 
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- ## Related work
 
 
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- If you are interested in related datasets (or models), check out the MU-NLPC organization here on HuggingFace. We have released a few other datasets in a compatible format, and several models that use an external calculator during inference.
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  ## Cite
@@ -119,7 +130,7 @@ If you use this dataset in research, please cite the original [ASDiv paper](http
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  title = "Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems",
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  author = "Marek Kadlčík and Michal Štefánik and Ondřej Sotolář and Vlastimil Martinek",
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  booktitle = "Proceedings of the The 2023 Conference on Empirical Methods in Natural Language Processing: Main track",
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- month = december,
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  year = "2023",
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  address = "Singapore, Singapore",
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  publisher = "Association for Computational Linguistics",
 
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  This dataset presents in-context scenarios where models can outsource the computations in the reasoning chain to a calculator.
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+ ## Data splits
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+
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+ The dataset does not contain data splits. We consider the whole dataset as a testing benchmark.
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+
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+
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  ## Attributes:
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+ - **id**: id of the example
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+ - **question** problem description in English
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+ - **chain**: series of simple operations (derived from **expression**) that lead to the solution
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+ - **result**: the solution for x as a number or fraction (string)
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+ - **result_float**: same as **result** but converted to a float
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+ - **result_unit**: the units of the result
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+ - **grade**: an estimate of the school grade in which the problem would be practiced
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+ - **source_question**: the source from which the example originates
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+ Attributes **id**, **question**, **chain**, and **result** are present in all datasets in the [Calc-X collection](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483).
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+ ## Related work
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+ This dataset was created as a part of a larger effort in training models capable of using a calculator during inference, which we call Calcformers.
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+ - [**Calc-X collection**](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483) - datasets for training Calcformers
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+ - [**Calcformers collection**](https://huggingface.co/collections/MU-NLPC/calcformers-65367392badc497807b3caf5) - calculator-using models we trained and published on HF
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+ - [**Calc-X and Calcformers paper**](https://arxiv.org/abs/2305.15017)
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+ - [**Calc-X and Calcformers repo**](https://github.com/prompteus/calc-x)
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+ Here are links to the original dataset:
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+ - [**original ASDiv dataset and repo**](https://github.com/chaochun/nlu-asdiv-dataset)
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+ - [**original ASDiv paper**](https://aclanthology.org/2020.acl-main.92)
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+ ## Licence
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+
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+ CC BY-NC 4.0, consistent with the original source dataset linked above.
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  ## Cite
 
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  title = "Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems",
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  author = "Marek Kadlčík and Michal Štefánik and Ondřej Sotolář and Vlastimil Martinek",
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  booktitle = "Proceedings of the The 2023 Conference on Empirical Methods in Natural Language Processing: Main track",
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+ month = dec,
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  year = "2023",
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  address = "Singapore, Singapore",
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  publisher = "Association for Computational Linguistics",