% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").

@article{huang2023numhg,
  title={NumHG: A Dataset for Number-Focused Headline Generation},
  author={Huang, Jian-Tao and Chen, Chung-Chi and Huang, Hen-Hsen and Chen, Hsin-Hsi},
  journal={arXiv preprint arXiv:2309.01455},
  year={2023}
}

@misc{jiang2023mistral,
      title={Mistral 7B}, 
      author={Albert Q. Jiang and Alexandre Sablayrolles and Arthur Mensch and Chris Bamford and Devendra Singh Chaplot and Diego de las Casas and Florian Bressand and Gianna Lengyel and Guillaume Lample and Lucile Saulnier and Lélio Renard Lavaud and Marie-Anne Lachaux and Pierre Stock and Teven Le Scao and Thibaut Lavril and Thomas Wang and Timothée Lacroix and William El Sayed},
      year={2023},
      eprint={2310.06825},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{rafailov2023direct,
      title={Direct Preference Optimization: Your Language Model is Secretly a Reward Model}, 
      author={Rafael Rafailov and Archit Sharma and Eric Mitchell and Stefano Ermon and Christopher D. Manning and Chelsea Finn},
      year={2023},
      eprint={2305.18290},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@article{DBLP:journals/corr/abs-1910-13461,
  author       = {Mike Lewis and
                  Yinhan Liu and
                  Naman Goyal and
                  Marjan Ghazvininejad and
                  Abdelrahman Mohamed and
                  Omer Levy and
                  Veselin Stoyanov and
                  Luke Zettlemoyer},
  title        = {{BART:} Denoising Sequence-to-Sequence Pre-training for Natural Language
                  Generation, Translation, and Comprehension},
  journal      = {CoRR},
  volume       = {abs/1910.13461},
  year         = {2019},
  url          = {http://arxiv.org/abs/1910.13461},
  eprinttype    = {arXiv},
  eprint       = {1910.13461},
  timestamp    = {Thu, 31 Oct 2019 14:02:26 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1910-13461.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@misc{dettmers2023qlora,
      title={QLoRA: Efficient Finetuning of Quantized LLMs}, 
      author={Tim Dettmers and Artidoro Pagnoni and Ari Holtzman and Luke Zettlemoyer},
      year={2023},
      eprint={2305.14314},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@inproceedings{numeval-report,
    title={SemEval-2024 Task 7: Numeral-Aware Language Understanding and Generation},
    author={Chen, Chung-Chi and Huang, Jian-Tao and Huang, Hen-Hsen and Takamura, Hiroya and Chen, Hsin-Hsi},
    booktitle={Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)},
    year={2024},
    publisher={Association for Computational Linguistics},
}


@article{DBLP:journals/corr/abs-1912-08777,
  author       = {Jingqing Zhang and
                  Yao Zhao and
                  Mohammad Saleh and
                  Peter J. Liu},
  title        = {{PEGASUS:} Pre-training with Extracted Gap-sentences for Abstractive
                  Summarization},
  journal      = {CoRR},
  volume       = {abs/1912.08777},
  year         = {2019},
  url          = {http://arxiv.org/abs/1912.08777},
  eprinttype    = {arXiv},
  eprint       = {1912.08777},
  timestamp    = {Fri, 03 Jan 2020 16:10:45 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1912-08777.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/abs-2010-08014,
  author       = {Zi{-}Yi Dou and
                  Pengfei Liu and
                  Hiroaki Hayashi and
                  Zhengbao Jiang and
                  Graham Neubig},
  title        = {GSum: {A} General Framework for Guided Neural Abstractive Summarization},
  journal      = {CoRR},
  volume       = {abs/2010.08014},
  year         = {2020},
  url          = {https://arxiv.org/abs/2010.08014},
  eprinttype    = {arXiv},
  eprint       = {2010.08014},
  timestamp    = {Mon, 23 Nov 2020 08:36:39 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2010-08014.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:journals/corr/BahdanauCB14,
  author       = {Dzmitry Bahdanau and
                  Kyunghyun Cho and
                  Yoshua Bengio},
  editor       = {Yoshua Bengio and
                  Yann LeCun},
  title        = {Neural Machine Translation by Jointly Learning to Align and Translate},
  booktitle    = {3rd International Conference on Learning Representations, {ICLR} 2015,
                  San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings},
  year         = {2015},
  url          = {http://arxiv.org/abs/1409.0473},
  timestamp    = {Wed, 17 Jul 2019 10:40:54 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/BahdanauCB14.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/corr/RushCW15,
  author       = {Alexander M. Rush and
                  Sumit Chopra and
                  Jason Weston},
  title        = {A Neural Attention Model for Abstractive Sentence Summarization},
  journal      = {CoRR},
  volume       = {abs/1509.00685},
  year         = {2015},
  url          = {http://arxiv.org/abs/1509.00685},
  eprinttype    = {arXiv},
  eprint       = {1509.00685},
  timestamp    = {Mon, 13 Aug 2018 16:46:49 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/RushCW15.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{nallapati-etal-2016-abstractive,
    title = "Abstractive Text Summarization using Sequence-to-sequence {RNN}s and Beyond",
    author = "Nallapati, Ramesh  and
      Zhou, Bowen  and
      dos Santos, Cicero  and
      Gu̇l{\c{c}}ehre, {\c{C}}a{\u{g}}lar  and
      Xiang, Bing",
    editor = "Riezler, Stefan  and
      Goldberg, Yoav",
    booktitle = "Proceedings of the 20th {SIGNLL} Conference on Computational Natural Language Learning",
    month = aug,
    year = "2016",
    address = "Berlin, Germany",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/K16-1028",
    doi = "10.18653/v1/K16-1028",
    pages = "280--290",
}


@inproceedings{dorr-etal-2003-hedge,
    title = "Hedge Trimmer: A Parse-and-Trim Approach to Headline Generation",
    author = "Dorr, Bonnie  and
      Zajic, David  and
      Schwartz, Richard",
    booktitle = "Proceedings of the {HLT}-{NAACL} 03 Text Summarization Workshop",
    year = "2003",
    url = "https://aclanthology.org/W03-0501",
    pages = "1--8",
}

@article{DBLP:journals/corr/abs-1109-2128,
  author       = {G{\"{u}}nes Erkan and
                  Dragomir R. Radev},
  title        = {LexRank: Graph-based Lexical Centrality as Salience in Text Summarization},
  journal      = {CoRR},
  volume       = {abs/1109.2128},
  year         = {2011},
  url          = {http://arxiv.org/abs/1109.2128},
  eprinttype    = {arXiv},
  eprint       = {1109.2128},
  timestamp    = {Mon, 13 Aug 2018 16:48:09 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1109-2128.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{mihalcea-tarau-2004-textrank,
    title = "{T}ext{R}ank: Bringing Order into Text",
    author = "Mihalcea, Rada  and
      Tarau, Paul",
    editor = "Lin, Dekang  and
      Wu, Dekai",
    booktitle = "Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing",
    month = jul,
    year = "2004",
    address = "Barcelona, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W04-3252",
    pages = "404--411",
}

@inproceedings{wang-etal-2022-salience,
    title = "Salience Allocation as Guidance for Abstractive Summarization",
    author = "Wang, Fei  and
      Song, Kaiqiang  and
      Zhang, Hongming  and
      Jin, Lifeng  and
      Cho, Sangwoo  and
      Yao, Wenlin  and
      Wang, Xiaoyang  and
      Chen, Muhao  and
      Yu, Dong",
    editor = "Goldberg, Yoav  and
      Kozareva, Zornitsa  and
      Zhang, Yue",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.emnlp-main.409",
    doi = "10.18653/v1/2022.emnlp-main.409",
    pages = "6094--6106",
    abstract = "Abstractive summarization models typically learn to capture the salient information from scratch implicitly. Recent literature adds extractive summaries as guidance for abstractive summarization models to provide hints of salient content and achieves better performance. However, extractive summaries as guidance could be over strict, leading to information loss or noisy signals. Furthermore, it cannot easily adapt to documents with various abstractiveness. As the number and allocation of salience content pieces varies, it is hard to find a fixed threshold deciding which content should be included in the guidance. In this paper, we propose a novel summarization approach with a flexible and reliable salience guidance, namely SEASON (SaliencE Allocation as Guidance for Abstractive SummarizatiON).SEASON utilizes the allocation of salience expectation to guide abstractive summarization and adapts well to articles in different abstractiveness. Automatic and human evaluations on two benchmark datasets show that the proposed method is effective and reliable. Empirical results on more than one million news articles demonstrate a natural fifteen-fifty salience split for news article sentences, providing a useful insight for composing news articles.",
}