pip install -r requirements.txt

python run.py --input_file data/summary/sumdata/Giga/input.txt --config configs/hc_title_8.yaml --output_dir outputs/hc_title_8

python outputs/evaluate.py --output_dir outputs/hc_title_8/ --reference_file data/summary/sumdata/Giga/task1_ref0.txt

python lm/language_model.py --input_file path_to_data/train.title.txt --valid_file path_to_data/valid.title.filter.small.txt --vocab_file lm/vocabs/title.vocab --config_file lm/configs/title_forward.yaml --save_dir lm/outputs/title_forward

./fasttext sent2vec -input data/train.title.txt -output title -minCount 5 -dim 700 -epoch 20 -lr 0.2 -wordNgrams 1 -loss ns -neg 10 -thread 20 -t 0.000005 -dropoutK 4 -minCountLabel 20 -bucket 4000000 -maxVocabSize 70000 -numCheckPoints 1

python scripts/sent2vec_model_to_numpy.py --s2v_model title.bin --vocab_file title.vocab --output_file embeddings/s2v_title.npy

@inproceedings{schumann-etal-2020-discrete,
    title = "Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction",
    author = "Schumann, Raphael and Mou, Lili and Lu, Yao and Vechtomova, Olga and Markert, Katja",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    year = "2020",
    month = jul,
    address = "Online",
    publisher = "Association for Computational Linguistics",
    doi = "10.18653/v1/2020.acl-main.452",
    pages = "5032--5042"
}