README.md

---
configs:
- config_name: CA
  data_files:
  - split: test
    path:
    - Task1(CA).csv
- config_name: DS
  data_files:
  - split: test
    path:
    - Task2(DS).csv
- config_name: CQ
  data_files:
  - split: test
    path:
    - Task3(CQ).csv
- config_name: FiB
  data_files:
  - split: test
    path:
    - Task4(FiB).csv
- config_name: QNLI
  data_files:
  - split: test
    path:
    - Task5(QNLI).csv
- config_name: AWP
  data_files:
  - split: test
    path:
    - Task6(AWP).csv
license: mit
language:
- bn
pretty_name: BenNumEval
size_categories:
- 1K<n<10K
---


# BenNumEval: A Benchmark to Assess LLM’s Numerical Reasoning Capabilities in Bengali

**BenNumEval** is a novel benchmark designed to evaluate the numerical reasoning abilities of Large Language Models (LLMs) in the Bengali language. It introduces six diverse task categories and a high-quality dataset containing over 3,200 examples derived from educational and real-world sources.

## 📁 Dataset Overview

BenNumEval includes **3,255** curated examples divided into six task types:

| Task Type                      | Description                                                                 | Examples |
|-------------------------------|-----------------------------------------------------------------------------|----------|
| Commonsense + Arithmetic (CA) | Problems combining arithmetic with common-sense knowledge                   | 410      |
| Domain-Specific (DS)          | Problems requiring domain knowledge (e.g., physics, chemistry, CS)          | 705      |
| Commonsense + Quantitative (CQ) | Simple comparisons based on everyday logic                                 | 400      |
| Fill-in-the-Blanks (FiB)      | Arithmetic word problems in fill-in-the-blank style                         | 665      |
| Quantitative NLI (QNLI)       | Natural language inference involving numerical understanding                | 425      |
| Arithmetic Word Problems (AWP)| Real-world word problems requiring arithmetic reasoning                     | 650      |


# Code Snipet to Download the dataset

Install the datasets library if you've not installed yet.
```
pip install datasets
```

Then load the dataset

```python
from datasets import load_dataset

dataset = load_dataset("ka05ar/BenNumEval", 'CA') #for downloading Task1(CA) subset
```

## 📜 Citation

If you use **BenNumEval** in your work, please cite:

```bibtex
@inproceedings{ahmed2025bennumeval,
  title={BenNumEval: A Benchmark to Assess LLMs’ Numerical Reasoning Capabilities in Bengali},
  author={Ahmed, Kawsar and Osama, Md and Sharif, Omar and Hossain, Eftekhar and Hoque, Mohammed Moshiul},
  booktitle={Findings of the Association for Computational Linguistics: ACL 2025},
  pages={17782--17799},
  year={2025}
}
```