Update README.md

README.md

@@ -83,23 +83,30 @@ parsed (e.g. by BeautifulSoup). The data contains 3 types of tags:
 - result: The final answer to the mathematical problem (a number)
 
 
-##  Supported Tasks
+## Supported Tasks
 
 This variant of the dataset is intended for training Chain-of-Thought reasoning models able to use external tools to enhance the factuality of their responses.
 This dataset presents in-context scenarios where models can outsource the computations in the reasoning chain to a calculator.
 
 
-## Features:
+## Construction process
 
-- `id`: problem id from the original dataset
-- `question`: the question intended to answer
-- `chain`: series of simple operations (derived from `equation`) that leads to the solution
-- `result`: the result (number) as a string
-- `result_float`: result converted to a floating point
-- `equation`: a nested expression that evaluates to the correct result
-- `problem_type`: a category of the problem
+We created the dataset by converting the **equation** attribute in the original dataset to a sequence (chain) of calculations, with final one being the result to the math problem.
+We also perform in-dataset and cross-dataset data-leak detection within the [Calc-X collection](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483).
+However, for SVAMP specifically, we detected no data leaks and filtered no data.
 
-Features `id`, `question`, `chain`, and `result` are present in all datasets in [Calc-X collection](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483).
+
+## Attributes:
+
+- **id**: problem id from the original dataset
+- **question**: the question intended to answer
+- **chain**: series of simple operations (derived from `equation`) that leads to the solution
+- **result**: the result (number) as a string
+- **result_float**: result converted to a floating point
+- **equation**: a nested expression that evaluates to the correct result
+- **problem_type**: a category of the problem
+
+Attributes **id**, **question**, **chain**, and **result** are present in all datasets in [Calc-X collection](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483).
 
 
 ## Content and data splits
@@ -108,19 +115,29 @@ The dataset contains the same data instances as the original dataset except for
 To the best of our knowledge, the original dataset does not contain an official train-test split. We treat the whole dataset as a testing benchmark.
 
 
-## Licence
+## Related work
 
-MIT, consistent with the original source dataset linked above.
+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.
 
+- [**Calc-X collection**](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483) - datasets for training Calcformers
+- [**Calcformers collection**](https://huggingface.co/collections/MU-NLPC/calcformers-65367392badc497807b3caf5) - calculator-using models we trained and published on HF
+- [**Calc-X and Calcformers paper**](https://arxiv.org/abs/2305.15017)
+- [**Calc-X and Calcformers repo**](https://github.com/prompteus/calc-x)
+
+Here are links to the original dataset:
+
+- [**original SVAMP dataset and repo**](https://github.com/arkilpatel/SVAMP/)
+- [**original SVAMP paper**](https://www.semanticscholar.org/paper/Are-NLP-Models-really-able-to-Solve-Simple-Math-Patel-Bhattamishra/13c4e5a6122f3fa2663f63e49537091da6532f35)
 
-## Related work
 
-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 external calculator during inference.
+## Licence
+
+MIT, consistent with the original source dataset linked above.
 
 
 ## Cite
 
-If you use this version of dataset in research, please cite the original [SVAMP paper](https://www.semanticscholar.org/paper/Are-NLP-Models-really-able-to-Solve-Simple-Math-Patel-Bhattamishra/13c4e5a6122f3fa2663f63e49537091da6532f35) and [Calc-X collection](https://arxiv.org/abs/2305.15017) as follows:
+If you use this version of dataset in research, please cite the original [SVAMP paper](https://www.semanticscholar.org/paper/Are-NLP-Models-really-able-to-Solve-Simple-Math-Patel-Bhattamishra/13c4e5a6122f3fa2663f63e49537091da6532f35), and [Calc-X collection](https://arxiv.org/abs/2305.15017) as follows:
 
 ```bibtex
 @inproceedings{kadlcik-etal-2023-soft,