This is the official code implementation for SIGIR 23 Short Paper: A Lightweight Constrained Generation Alternative for Query-focused Summarization
A significant part of this code repo comes from Neurological Decoding Code Repo
pip3 install -r requirements.txt
Download the processed dataset and neural retrieval model from Link
need to configure the path and hyperparameters accordingly, a sample bash file is
bash run_finetune.sh
need to configure the path and hyperparameters accordingly, a sample bash file is
bash run_decode.sh
@inproceedings{xu-cohen-2023-lightweight,
author = {Xu, Zhichao and Cohen, Daniel},
title = {A Lightweight Constrained Generation Alternative for Query-Focused Summarization},
year = {2023},
isbn = {9781450394086},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3539618.3591936},
doi = {10.1145/3539618.3591936},
booktitle = {Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {1745–1749},
numpages = {5},
keywords = {query-focused summarization, constrained generation},
location = {Taipei, Taiwan},
series = {SIGIR '23}
}
@inproceedings{lu-etal-2021-neurologic,
title = "{N}euro{L}ogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints",
author = "Lu, Ximing and West, Peter and Zellers, Rowan and Le Bras, Ronan and Bhagavatula, Chandra and Choi, Yejin",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-main.339",
doi = "10.18653/v1/2021.naacl-main.339",
pages = "4288--4299",
}