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---
configs:
- config_name: default
data_files:
- split: train
path: benchmark.csv
dataset_info:
features:
- name: question_idx
dtype: int64
- name: question
dtype: string
- name: answer
dtype: int64
- name: word
dtype: string
- name: character
dtype: string
- name: task
dtype: string
---
# CharBench - Character-level benchmark and analysis suite for LLMs.
CharBench is a large-scale benchmark for studying tokenization and character-level behavior in modern language models.
For complete details on data curation and evaluation, see the [paper](https://arxiv.org/abs/2508.02591).
If you have ideas and suggestions to improve charbench feel free to reach out!
uzan dot omri at gmail.com
## Usage
```python
from datasets import load_dataset
ds = load_dataset("omriuz/CharBench")
```
## Citation
If you use CharBench, please cite:
```
@inproceedings{uzan2026charbench,
title = {CharBench: Evaluating the Role of Tokenization in Character-Level Tasks},
author = {Uzan, Omri and Pinter, Yuval},
booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
year = {2026},
address = {Singapore},
note = {AAAI-26},
eprint = {2508.02591},
archivePrefix = {arXiv},
primaryClass = {cs.CL},
url = {https://arxiv.org/abs/2508.02591}
}
``` |