IDEAL_Summary

IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization

Data Processing

1. Download datasets from their respective official repositories:

   • SQuALITY
   • CovidET
   • QMSum

2. Preprocess the datasets using the provided Jupyter notebook: data_process.ipynb.

Training, Inference, and Evaluation

To train, run inference, and evaluate the model, execute the following script:

bash exps/finetuning_*_generate_evaluate.sh

For multi-reference Rouge scores and Bart-score evaluations on the SQuALITY dataset, use the notebook multi_reference_evaluation_SQuAlITY.ipynb.

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