---
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}
}

```