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--- |
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license: cc-by-sa-4.0 |
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language: |
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- en |
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tags: |
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- citation |
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- scientific paper |
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- grounding |
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- source attribution |
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- paper citations |
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- citation benchmark |
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- text benchmark |
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--- |
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# CiteME is a benchmark designed to test the abilities of language models in finding papers that are cited in scientific texts.# |
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## Dataset Structure |
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The dataset is provided in CSV format and includes the following columns: |
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| Column Name | Description | |
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|----------------------|------------------------------------------------------| |
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| `id` | A unique identifier for each paper, used consistently across all experiments. | |
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| `excerpt` | The text excerpt from the source paper that describes the target paper. | |
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| `target_paper_title` | The title of the paper that is being cited in the excerpt. | |
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| `target_paper_url` | The URL linking to the target paper. | |
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| `source_paper_title` | The title of the paper from which the excerpt is taken. | |
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| `source_paper_url` | The URL linking to the source paper. | |
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| `year` | The publication year of the source paper. | |
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| `split` | Indicates the dataset split: `train` or `test`. | |
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### Example |
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| id | excerpt | target_paper_title | target_paper_url | source_paper_title | source_paper_url | year | split | |
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|-----|---------------------------------------------------------------------------------------------------|--------------------------------------|----------------------------------------|------------------------------------|--------------------------------------|------|-------| |
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| 1 | "As demonstrated in [Smith et al., 2020], the proposed method improves accuracy significantly." | "Improving Accuracy in ML Models" | https://example.com/target1 | "Advancements in Machine Learning" | https://example.com/source1 | 2020 | train | |
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| 2 | "Building upon the framework introduced by [Doe, 2019], we extend the applicability to NLP tasks." | "Framework for NLP Applications" | https://example.com/target2 | "Foundations of NLP" | https://example.com/source2 | 2019 | test | |
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### Load the Dataset |
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You can load the dataset using popular data processing libraries such as `pandas`. |
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```python |
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import pandas as pd |
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dataset = pd.read_csv('DATASET.csv') |
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print(dataset.head()) |
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``` |
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### If you find our work helpful, please use the following citation: |
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``` |
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@misc{press2024citeme, |
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title={CiteME: Can Language Models Accurately Cite Scientific Claims?}, |
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author={Ori Press and Andreas Hochlehnert and Ameya Prabhu and Vishaal Udandarao and Ofir Press and Matthias Bethge}, |
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year={2024}, |
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eprint={2407.12861}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.AI}, |
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url={https://arxiv.org/abs/2407.12861} |
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} |
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``` |
