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  ---
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  language:
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  - en
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- - ar
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  license: mit
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  size_categories:
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  - 1K<n<10K
@@ -109,17 +108,6 @@ 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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-
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- - `id`: id of the example
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- - `question`: problem description in English
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- - `question_arabic`: problem description in Arabic
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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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- - `equation`: an equation that needs to be solved for `x` to obtain the result. Usually in the form of "x = ..." but not always.
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- - `expression`: arithmetic expression derived from `equation` that solves it for `x`
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-
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  ## Data splits
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@@ -137,15 +125,40 @@ datasets.load_dataset("MU-NLPC/calc-mawps")
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  ```
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- ## Licence
 
 
 
 
 
 
 
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- MIT, 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
@@ -157,7 +170,7 @@ If you use this version of the dataset in research, please cite the original [MA
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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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  ---
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  language:
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  - en
 
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  license: mit
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  size_categories:
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  - 1K<n<10K
 
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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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+ ## Attributes:
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+ - **id**: id of the example
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+ - **question**: problem description in English
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+ - **question_arabic**: problem description in Arabic
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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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+ - **equation**: an equation that needs to be solved for `x` to obtain the result. Usually in the form of "x = ..." but not always.
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+ - **expression**: arithmetic expression derived from `equation` that solves it for `x`
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+ Attributes **id**, **question**, **chain**, and **result** are present in all datasets in [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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+
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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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+
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+ Here are links to the original dataset:
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+
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+ - [**original MAWPS dataset**](http://lang.ee.washington.edu/MAWPS)
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+ - [**MAWPS dataset variant in Arabic**](https://huggingface.co/datasets/omarxadel/MaWPS-ar)
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+ - [**original MAWPS paper**](https://aclanthology.org/N16-1136/)
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+ - [**original MAWPS repo**](https://github.com/sroy9/mawps)
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+
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+
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+ ## Licence
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+
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+ MIT, 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",