metadata
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.
If you have ideas and suggestions to improve charbench feel free to reach out! uzan dot omri at gmail.com
Usage
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}
}