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XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates

Conference arXiv

This repository contains the dataset reproduction scripts for XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates.

xatu

Citations

@inproceedings{zhang24coling,
    title = {{XATU}: {A} {F}ine-grained {I}nstruction-based {B}enchmark for {E}xplainable {T}ext {U}pdates},
    author = {Haopeng Zhang and
              Hayate Iso and
              Sairam Gurajada and
              Nikita Bhutani},
    booktitle = {LREC-COLING},
    month = {May},
    year = {2024}
}

XATU setup

Install dependencies, download all the raw dataset, and then build XATU.

pip install -r requirements.txt
bash ./scripts/setup_data.sh
python ./scripts/setup.py --output_path ./data/xatu.jsonl

Disclosure

Embedded in, or bundled with, this product are open source software (OSS) components, datasets and other third party components identified below. The license terms respectively governing the datasets and third-party components continue to govern those portions, and you agree to those license terms, which, when applicable, specifically limit any distribution. You may receive a copy of, distribute and/or modify any open source code for the OSS component under the terms of their respective licenses, which may be BSD 3 clause license and Apache 2.0 license. In the event of conflicts between Megagon Labs, Inc., license conditions and the Open Source Software license conditions, the Open Source Software conditions shall prevail with respect to the Open Source Software portions of the software. You agree not to, and are not permitted to, distribute actual datasets used with the OSS components listed below. You agree and are limited to distribute only links to datasets from known sources by listing them in the datasets overview table below. You are permitted to distribute derived datasets of data sets from known sources by including links to original dataset source in the datasets overview table below. You agree that any right to modify datasets originating from parties other than Megagon Labs, Inc. are governed by the respective third party’s license conditions. All OSS components and datasets are distributed WITHOUT ANY WARRANTY, without even implied warranty such as for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE, and without any liability to or claim against any Megagon Labs, Inc. entity other than as explicitly documented in this README document. You agree to cease using any part of the provided materials if you do not agree with the terms or the lack of any warranty herein. While Megagon Labs, Inc., makes commercially reasonable efforts to ensure that citations in this document are complete and accurate, errors may occur. If you see any error or omission, please help us improve this document by sending information to contact_oss@megagon.ai.

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🕊️ Code and Data for XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates (Zhang et al; LREC-COLING 2024)

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