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---
license: cc-by-sa-4.0
task_categories:
- text-generation
language:
- en
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---
# AbsenceBench: Language Models Can't Tell What's Missing
[[paper]](https://arxiv.org/abs/2506.11440) [[code]](https://github.com/harvey-fin/absence-bench)
# Dataset Card for AbsenceBench
AbsenceBench covers three distinct domains:
- Poetry (realistic)
- Numerical sequences (synthetic)
- GitHub pull requests (realistic)
There are 4302 instances in total, with an average context length of 5K tokens.
## Data Structure
Each domain contains the following features:
- `original_context`: `string`
- `modified_context`: `string`
- `omitted_context`: `List[string]`
- `omitted_index`: `List[int]`
- `metadata`: `Dict` Extra information regarding the dataset generation
### Data Split
Currently we provide only the `validation` split. Since all instances of AbsenceBench natually come up with labeled answers according to the task setting, we will not be able to provide an unlabeled `test` split.
## Dataset Construction
We provide the source data for generating the poetry domain, originally from the [Gutenberg Poetry Corpus](https://github.com/aparrish/gutenberg-poetry-corpus) in the `poetry_raw` subset.
Please refer to this [repo](https://github.com/harvey-fin/absence-bench) for scripts and more information.
## Citation
If you find this work useful, please cite our paper:
```Bibtex
@misc{fu2025absencebenchlanguagemodelscant,
title={AbsenceBench: Language Models Can't Tell What's Missing},
author={Harvey Yiyun Fu and Aryan Shrivastava and Jared Moore and Peter West and Chenhao Tan and Ari Holtzman},
year={2025},
eprint={2506.11440},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2506.11440},
}
```
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