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Few-shot Event Detection: An Empirical Study and a Unified View

This is the implementation of the paper Few-shot Event Detection: An Empirical Study and a Unified View. ACL'2023.

Data

See details in dataset_processing pages

Requirements

  • python 3.8.12
  • Pytorch 1.7.0
  • Transformers 4.10.0

You can install other dependencies by pip install -r requirements.txt

Code

Simplified source code (version 1). It includes the core parts of our work (i.e., the unified baseline proposed). The authors would find time cleaning the remaining code and make it publicly available as soon as possible.

To run this code,

DATA=[ACE|MAVEN|ERE] K=[2|5|10] idx=[0|1|2|3|4|5|6|7|8|9] bash run.sh

Citation

Please cite our paper if you use it in your work:

@misc{ma2023fewshot,
      title={Few-shot Event Detection: An Empirical Study and a Unified View}, 
      author={Yubo Ma and Zehao Wang and Yixin Cao and Aixin Sun},
      year={2023},
      eprint={2305.01901},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

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ACL'2023: Few-shot Event Detection: An Empirical Study and a Unified View

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