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Source code for paper: HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction

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Introduction

Hierarchical information extraction Network (HiNet)

Source code for paper: HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction

Model architecture:

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Bibtex:

@article{Zhou2023HiNet,
  title={HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction},
  author={Zhou, Jie and Cao, Xianshuai and Li, Wenhao and Bo, Lin and Luo, Chuan and Yu, Qian,
  year={2023},
}

Requirements

Python >= 3.7
Tensorflow >= 1.15.0

Train and Evaluate Model

python -u HiNet.py --config_file_path=../config/hinet_sample_schemas.json --task_type=train

You can modify the "FLAGS" parameters as needed.

Acknowledgement

  • The work is supported by MeiTuan.
  • The work is also supported by the National Natural Science Foundation of China (No. 62202025 and 62002012).

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