HiPool

This is the pyTorch implementation of HiPool: Hierarchical Pooling for Long Document Classification, published in ACL 2023.

The code is based on this implementation: git link

Install

Tested on python 3.8.8.

conda env create -f environment.yml

Running

CUDA_VISIBLE_DEVICES=1 python train_imdb.py --sentlen 50 --adj_method bigbird --level sent --graph_type gat --epoch 10

default dataset: consumer_complaints

Main Scripts

train_imdb.py: main function.

Dataset_Split_Class.py: data loading.

Bert_Classification.py: modeling for BERT and graphs.

Graph_Models.py: graph model classes.

Graph_Models_utils.py: helper functions for graph model classes.

Cite this work

@inproceedings{li2023hipool,
  title={HiPool: Modeling Long Documents Using Graph Neural Networks},
  author={Li, Irene and Feng, Aosong and Radev, Dragomir and Ying, Rex},
  booktitle={Proceedings of the Association for Computational Linguistics (ACL)},
  year={2023},
  url={https://arxiv.org/abs/2305.03319}
}