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