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---
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license: mit
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---
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# HARDMath2 Benchmark Dataset
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This repository contains a collection of mathematical benchmark problems designed for evaluating Large Language Models (LLMs) on mathematical reasoning tasks.
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## Building
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Save `.csv` file exported from Google Sheet to `raw_csv` folder and run `csv_to_yaml.py` to convert all of the `.csv` file sto `.yaml`. Then push the changes to remote and the `.yaml` file will automatically be converted to `.jsonl` and pushed to an anonymized HF repository.
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The `.csv` file should have a descriptive name for the types of problems in the file, with underscores instead of spaces.
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## Data Format
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Each benchmark problem in the dataset is structured as a JSON object containing the following fields:
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### Fields
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- **Prompt**: The input string that is fed to the LLM
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- **Solution**: A LaTeX-formatted string representing the mathematical formula that solves the question posed in the prompt
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- **Parameters**: A list of independent tokens that should be treated as single variables in the LaTeX response string. These include:
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- Single variables (e.g., `$A$`, `$x$`)
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- Greek letters (e.g., `$\epsilon$`)
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- Complex strings with subscripts (e.g., `$\delta_{i,j}$`)
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Each parameter should be separated by a semicolon (;).
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## Example
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```json
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{
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"prompt": "What is the derivative of f(x) = x^2?",
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"solution": "\\frac{d}{dx}(x^2) = 2x",
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"parameters": "x"
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}
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``` |
