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RADGen

RADGen(REINFORCE Aided Deep Generator for news headline)
Aobo Xu, Ling Jian. A Deep News Headline Generation Model with REINFORCE Filter. 2023 International Joint Conference on Neural Networks (IJCNN).IEEE, 2023. (DOI: 10.1109/IJCNN54540.2023.10192007)

Package Requirement

tensorflow==2.4.1
wandb==0.12.2
rouge==1.0.1
numpy==1.19.5
pandas=1.1.1

Code Running Order

1. tokenization.py

2. LoadDataChinese.py

3. TransformerChinese.py: Training Stage One

4. baseline_val.py, baseline_test.py, baseline_train.py

5. TrainRLChinese_R1.py, TrainRLChinese_R1_sample.py: Training Stage Two

Cite

BibTex
@inproceedings{xu2023deep, title={A Deep News Headline Generation Model with REINFORCE Filter}, author={Xu, Aobo and Jian, Ling}, booktitle={2023 International Joint Conference on Neural Networks (IJCNN)}, pages={1--7}, year={2023}, organization={IEEE} }

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