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
Tested on python 3.8.8.
conda env create -f environment.yml
CUDA_VISIBLE_DEVICES=1 python train_imdb.py --sentlen 50 --adj_method bigbird --level sent --graph_type gat --epoch 10
default dataset: consumer_complaints
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.
@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}
}