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One implementation of the paper "Controllable Neural Dialogue Summarization with Personal Named Entity Planning" (EMNLP 2022).

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Introduction

One implementation of the paper "Controllable Neural Dialogue Summarization with Personal Named Entity Planning" in EMNLP 2022.

Package Requirements

  1. pytorch==1.7.1
  2. transformers==4.8.2
  3. click==7.1.2
  4. sentencepiece==0.1.92
  5. allennlp==2.6.0
  6. allennlp-models==2.6.0

Training Data for Controllable Generation

The processed training data with the Occurrence Planning are located in ./data/SAMSum_data_OCC/.

Generated Summaries for SAMSum Corpus

See the predictions from the controllable summarization model of SAMSum test set in ./model_outputs/

Citation

@inproceedings{liu-chen-2021-controllable,
    title = "Controllable Neural Dialogue Summarization with Personal Named Entity Planning",
    author = "Liu, Zhengyuan and Chen, Nancy",
    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2021",
    address = "Online and Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.emnlp-main.8",
    pages = "92--106",
}

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One implementation of the paper "Controllable Neural Dialogue Summarization with Personal Named Entity Planning" (EMNLP 2022).

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