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



@article{SLOT-Framework--Yow-etal-2025,
  author       = {Darren Yow{-}Bang Wang and
                  Zhengyuan Shen and
                  Soumya Smruti Mishra and
                  Zhichao Xu and
                  Yifei Teng and
                  Haibo Ding},
  title        = {{SLOT:} Structuring the Output of Large Language Models},
  journal      = {CoRR},
  volume       = {abs/2505.04016},
  year         = {2025},
  url          = {https://doi.org/10.48550/arXiv.2505.04016},
  doi          = {10.48550/ARXIV.2505.04016},
  eprinttype    = {arXiv},
  eprint       = {2505.04016},
  timestamp    = {Fri, 20 Jun 2025 20:58:52 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2505-04016.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{Generated-Knowledge-prompting--Liu-etal-2022,
  author       = {Jiacheng Liu and
                  Alisa Liu and
                  Ximing Lu and
                  Sean Welleck and
                  Peter West and
                  Ronan Le Bras and
                  Yejin Choi and
                  Hannaneh Hajishirzi},
  editor       = {Smaranda Muresan and
                  Preslav Nakov and
                  Aline Villavicencio},
  title        = {Generated Knowledge Prompting for Commonsense Reasoning},
  booktitle    = {Proceedings of the 60th Annual Meeting of the Association for Computational
                  Linguistics (Volume 1: Long Papers), {ACL} 2022, Dublin, Ireland,
                  May 22-27, 2022},
  pages        = {3154--3169},
  publisher    = {Association for Computational Linguistics},
  year         = {2022},
  url          = {https://doi.org/10.18653/v1/2022.acl-long.225},
  doi          = {10.18653/V1/2022.ACL-LONG.225},
  timestamp    = {Sat, 29 Apr 2023 10:09:26 +0200},
  biburl       = {https://dblp.org/rec/conf/acl/0010LLWWBCH22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{Reason-and-Act-prompting--Yao-etal-2023,
  author       = {Shunyu Yao and
                  Jeffrey Zhao and
                  Dian Yu and
                  Nan Du and
                  Izhak Shafran and
                  Karthik R. Narasimhan and
                  Yuan Cao},
  title        = {ReAct: Synergizing Reasoning and Acting in Language Models},
  booktitle    = {The Eleventh International Conference on Learning Representations,
                  {ICLR} 2023, Kigali, Rwanda, May 1-5, 2023},
  publisher    = {OpenReview.net},
  year         = {2023},
  url          = {https://openreview.net/forum?id=WE\_vluYUL-X},
  timestamp    = {Wed, 24 Jul 2024 16:50:33 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/YaoZYDSN023.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}




@inproceedings{RAG--Lewis-etal-2020,
  author       = {Patrick Lewis and
                  Ethan Perez and
                  Aleksandra Piktus and
                  Fabio Petroni and
                  Vladimir Karpukhin and
                  Naman Goyal and
                  Heinrich K{\"{u}}ttler and
                  Mike Lewis and
                  Wen{-}tau Yih and
                  Tim Rockt{\"{a}}schel and
                  Sebastian Riedel and
                  Douwe Kiela},
  editor       = {Hugo Larochelle and
                  Marc'Aurelio Ranzato and
                  Raia Hadsell and
                  Maria{-}Florina Balcan and
                  Hsuan{-}Tien Lin},
  title        = {Retrieval-Augmented Generation for Knowledge-Intensive {NLP} Tasks},
  booktitle    = {Advances in Neural Information Processing Systems 33: Annual Conference
                  on Neural Information Processing Systems 2020, NeurIPS 2020, December
                  6-12, 2020, virtual},
  year         = {2020},
  url          = {https://proceedings.neurips.cc/paper/2020/hash/6b493230205f780e1bc26945df7481e5-Abstract.html},
  timestamp    = {Mon, 14 Apr 2025 22:19:00 +0200},
  biburl       = {https://dblp.org/rec/conf/nips/LewisPPPKGKLYR020.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{The-Llama-3-Herd-of-Models--MetaAI-2024,
  author       = {Abhimanyu Dubey and
                  Abhinav Jauhri and
                  Abhinav Pandey and
                  Abhishek Kadian and
                  Ahmad Al{-}Dahle and
                  Aiesha Letman and
                  Akhil Mathur and
                  Alan Schelten and
                  Amy Yang and
                  Angela Fan and
                  Anirudh Goyal and
                  Anthony Hartshorn and
                  Aobo Yang and
                  Archi Mitra and
                  Archie Sravankumar and
                  Artem Korenev and
                  Arthur Hinsvark and
                  Arun Rao and
                  Aston Zhang and
                  Aur{\'{e}}lien Rodriguez and
                  Austen Gregerson and
                  Ava Spataru and
                  Baptiste Rozi{\`{e}}re and
                  Bethany Biron and
                  Binh Tang and
                  Bobbie Chern and
                  Charlotte Caucheteux and
                  Chaya Nayak and
                  Chloe Bi and
                  Chris Marra and
                  Chris McConnell and
                  Christian Keller and
                  Christophe Touret and
                  Chunyang Wu and
                  Corinne Wong and
                  Cristian Canton Ferrer and
                  Cyrus Nikolaidis and
                  Damien Allonsius and
                  Daniel Song and
                  Danielle Pintz and
                  Danny Livshits and
                  David Esiobu and
                  Dhruv Choudhary and
                  Dhruv Mahajan and
                  Diego Garcia{-}Olano and
                  Diego Perino and
                  Dieuwke Hupkes and
                  Egor Lakomkin and
                  Ehab AlBadawy and
                  Elina Lobanova and
                  Emily Dinan and
                  Eric Michael Smith and
                  Filip Radenovic and
                  Frank Zhang and
                  Gabriel Synnaeve and
                  Gabrielle Lee and
                  Georgia Lewis Anderson and
                  Graeme Nail and
                  Gr{\'{e}}goire Mialon and
                  Guan Pang and
                  Guillem Cucurell and
                  Hailey Nguyen and
                  Hannah Korevaar and
                  Hu Xu and
                  Hugo Touvron and
                  Iliyan Zarov and
                  Imanol Arrieta Ibarra and
                  Isabel M. Kloumann and
                  Ishan Misra and
                  Ivan Evtimov and
                  Jade Copet and
                  Jaewon Lee and
                  Jan Geffert and
                  Jana Vranes and
                  Jason Park and
                  Jay Mahadeokar and
                  Jeet Shah and
                  Jelmer van der Linde and
                  Jennifer Billock and
                  Jenny Hong and
                  Jenya Lee and
                  Jeremy Fu and
                  Jianfeng Chi and
                  Jianyu Huang and
                  Jiawen Liu and
                  Jie Wang and
                  Jiecao Yu and
                  Joanna Bitton and
                  Joe Spisak and
                  Jongsoo Park and
                  Joseph Rocca and
                  Joshua Johnstun and
                  Joshua Saxe and
                  Junteng Jia and
                  Kalyan Vasuden Alwala and
                  Kartikeya Upasani and
                  Kate Plawiak and
                  Ke Li and
                  Kenneth Heafield and
                  Kevin Stone and
                  et al.},
  title        = {The Llama 3 Herd of Models},
  journal      = {CoRR},
  volume       = {abs/2407.21783},
  year         = {2024},
  url          = {https://doi.org/10.48550/arXiv.2407.21783},
  doi          = {10.48550/ARXIV.2407.21783},
  eprinttype    = {arXiv},
  eprint       = {2407.21783},
  timestamp    = {Tue, 08 Jul 2025 07:36:33 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2407-21783.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{QWEN2-Technical-Report--Alibaba-2024,
  author       = {An Yang and
                  Baosong Yang and
                  Binyuan Hui and
                  Bo Zheng and
                  Bowen Yu and
                  Chang Zhou and
                  Chengpeng Li and
                  Chengyuan Li and
                  Dayiheng Liu and
                  Fei Huang and
                  Guanting Dong and
                  Haoran Wei and
                  Huan Lin and
                  Jialong Tang and
                  Jialin Wang and
                  Jian Yang and
                  Jianhong Tu and
                  Jianwei Zhang and
                  Jianxin Ma and
                  Jianxin Yang and
                  Jin Xu and
                  Jingren Zhou and
                  Jinze Bai and
                  Jinzheng He and
                  Junyang Lin and
                  Kai Dang and
                  Keming Lu and
                  Keqin Chen and
                  Kexin Yang and
                  Mei Li and
                  Mingfeng Xue and
                  Na Ni and
                  Pei Zhang and
                  Peng Wang and
                  Ru Peng and
                  Rui Men and
                  Ruize Gao and
                  Runji Lin and
                  Shijie Wang and
                  Shuai Bai and
                  Sinan Tan and
                  Tianhang Zhu and
                  Tianhao Li and
                  Tianyu Liu and
                  Wenbin Ge and
                  Xiaodong Deng and
                  Xiaohuan Zhou and
                  Xingzhang Ren and
                  Xinyu Zhang and
                  Xipin Wei and
                  Xuancheng Ren and
                  Xuejing Liu and
                  Yang Fan and
                  Yang Yao and
                  Yichang Zhang and
                  Yu Wan and
                  Yunfei Chu and
                  Yuqiong Liu and
                  Zeyu Cui and
                  Zhenru Zhang and
                  Zhifang Guo and
                  Zhihao Fan},
  title        = {Qwen2 Technical Report},
  journal      = {CoRR},
  volume       = {abs/2407.10671},
  year         = {2024},
  url          = {https://doi.org/10.48550/arXiv.2407.10671},
  doi          = {10.48550/ARXIV.2407.10671},
  eprinttype    = {arXiv},
  eprint       = {2407.10671},
  timestamp    = {Wed, 27 Aug 2025 08:27:25 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2407-10671.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@ARTICLE{Prompting-Strategies-for-LLMs-in-Clinical-NLP-IE--Sivarajkumar-etal-2024,
	author = {Sivarajkumar, Sonish and Kelley, Mark and Samolyk-Mazzanti, Alyssa and Visweswaran, Shyam and Wang, Yanshan},
	title = {An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing: Algorithm Development and Validation Study},
	year = {2024},
	journal = {JMIR Medical Informatics},
	volume = {12},
	doi = {10.2196/55318},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191043200&doi=10.2196%2f55318&partnerID=40&md5=613a1c7af3cdea64f9e610a1a105c4b5},
	type = {Article},
	publication_stage = {Final},
	source = {Scopus},
	note = {Cited by: 58; All Open Access, Gold Open Access}
}

@article{Hallucinations-in-LLMs-Survey--Huang-etal-2025,
  author       = {Lei Huang and
                  Weijiang Yu and
                  Weitao Ma and
                  Weihong Zhong and
                  Zhangyin Feng and
                  Haotian Wang and
                  Qianglong Chen and
                  Weihua Peng and
                  Xiaocheng Feng and
                  Bing Qin and
                  Ting Liu},
  title        = {A Survey on Hallucination in Large Language Models: Principles, Taxonomy,
                  Challenges, and Open Questions},
  journal      = {{ACM} Trans. Inf. Syst.},
  volume       = {43},
  number       = {2},
  pages        = {42:1--42:55},
  year         = {2025},
  url          = {https://doi.org/10.1145/3703155},
  doi          = {10.1145/3703155},
  timestamp    = {Wed, 11 Jun 2025 21:01:33 +0200},
  biburl       = {https://dblp.org/rec/journals/tois/HuangYMZFWCPFQL25.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}



@article{Adressing-Biases-in-Gen-AI--Wei-etal-2025,
  author       = {Xiahua Wei and
                  Naveen Kumar and
                  Han Zhang},
  title        = {Addressing bias in generative {AI:} Challenges and research opportunities
                  in information management},
  journal      = {Inf. Manag.},
  volume       = {62},
  number       = {2},
  pages        = {104103},
  year         = {2025},
  url          = {https://doi.org/10.1016/j.im.2025.104103},
  doi          = {10.1016/J.IM.2025.104103},
  timestamp    = {Mon, 17 Feb 2025 15:44:02 +0100},
  biburl       = {https://dblp.org/rec/journals/iam/WeiKZ25.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@article{Collaborative-LLMs-for-data-extraction-in-living-systematic-reviews--Khan-etal-2025,
  author       = {Muhammad Ali Khan and
                  Umair Ayub and
                  Syed Arsalan Ahmed Naqvi and
                  Kaneez Zahra Rubab Khakwani and
                  Zaryab bin Riaz Sipra and
                  Ammad Raina and
                  Sihan Zhou and
                  Huan He and
                  Amir Saeidi and
                  Bashar Hasan and
                  Robert Bryan Rumble and
                  Danielle S. Bitterman and
                  Jeremy L. Warner and
                  Jia Zou and
                  Amye J. Tevaarwerk and
                  Konstantinos Leventakos and
                  Kenneth L. Kehl and
                  Jeanne M. Palmer and
                  Mohammad Hassan Murad and
                  Chitta Baral and
                  Irbaz Bin Riaz},
  title        = {Collaborative large language models for automated data extraction
                  in living systematic reviews},
  journal      = {J. Am. Medical Informatics Assoc.},
  volume       = {32},
  number       = {4},
  pages        = {638--647},
  year         = {2025},
  url          = {https://doi.org/10.1093/jamia/ocae325},
  doi          = {10.1093/JAMIA/OCAE325},
  timestamp    = {Wed, 11 Jun 2025 21:01:05 +0200},
  biburl       = {https://dblp.org/rec/journals/jamia/KhanANKSRZHSHRBWZTLKPMB25.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@ARTICLE{Extracting-Financial-Data-from-Unstructured-Leveraging-LLMs--Li-etal-2025,
	author = {Li, Huaxia and Gao, Haoyun and Wu, Chengzhang and Vasarhelyi, Miklos A.},
	title = {Extracting Financial Data from Unstructured Sources: Leveraging Large Language Models},
	year = {2025},
	journal = {Journal of Information Systems},
	volume = {39},
	number = {1},
	pages = {135 – 156},
	doi = {10.2308/ISYS-2023-047},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-86000537916&doi=10.2308%2fISYS-2023-047&partnerID=40&md5=05a490610021e0facc31e680fd116048},
	type = {Article},
	publication_stage = {Final},
	source = {Scopus},
	note = {Cited by: 5}
}




@ARTICLE{LLMs-for-Financial-and-Investment-Management--Kong-etal-2024,
	author = {Kong, Yaxuan and Nie, Yuqi and Dong, Xiaowen and Mulvey, John M. and Poor, H. Vincent and Wen, Qingsong and Zohren, Stefan},
	title = {Large Language Models for Financial and Investment Management: Applications and Benchmarks},
	year = {2024},
	journal = {Journal of Portfolio Management},
	volume = {51},
	number = {2},
	pages = {162 – 210},
	doi = {10.3905/jpm.2024.1.645},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211160907&doi=10.3905%2fjpm.2024.1.645&partnerID=40&md5=5b1b547f86a74fae65a01b2b897b5b31},
	type = {Article},
	publication_stage = {Final},
	source = {Scopus},
	note = {Cited by: 2}
}



@inproceedings{Attention-is-all-you-need--Vaswani-etal-2017,
author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N. and Kaiser, \L{}ukasz and Polosukhin, Illia},
title = {Attention is all you need},
year = {2017},
isbn = {9781510860964},
publisher = {Curran Associates Inc.},
address = {Red Hook, NY, USA},
abstract = {The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train. Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles, by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.0 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature.},
booktitle = {Proceedings of the 31st International Conference on Neural Information Processing Systems},
pages = {6000–6010},
numpages = {11},
location = {Long Beach, California, USA},
series = {NIPS'17}
}

@incollection{Boettcher1967_Vorwort,
  author       = {Böttcher, Kurt and Albrecht, Günter and Greiner-Mai, Herbert and Krohn, Paul Günter},
  title        = {Vorwort},
  booktitle    = {Lexikon deutschsprachiger Schriftsteller von den Anfängen bis zur Gegenwart},
  editor       = {Böttcher, K. and Albrecht, G. and Greiner-Mai, H. and Krohn, P. G.},
  publisher    = {VEB Bibliographisches Institut},
  address      = {Leipzig},
  year         = {1967},
  volume       = {Band 1},
  pages        = {5--7},
}

@article{Texts-into-Databases-New-style-Prosopography-Bradley-Harold-2005,
    author = {Bradley, John and Short, Harold},
    title = {Texts into Databases: The Evolving Field of New-style Prosopography},
    journal = {Literary and Linguistic Computing},
    volume = {20},
    number = {Suppl},
    pages = {3-24},
    year = {2005},
    month = {05},
    abstract = {In this article we discuss some issues that arise when a highly structural approach is taken to the development of prosopographies, based on our experience of three such projects. Databases in prosopography have traditionally been used to help a researcher analyse a large set of database-like historical materials—the database (Bulst, N. 1989, Prosopography and the Computer: Problems and Possibilities. In Mawdsley, E., Morgan, N., Richmond, L. and Trainor, R. (eds), History and Computing III. Manchester: Manchester University Press, pp. 12–18), acts as an intermediate aim, not a final one. For our prosopographical projects, the final prosopography is a highly structured database—not a set of articles derived, perhaps in part, from it. We have found that a highly structured model works well for our prosopographies when we use the database not to model the relevant content of the source materials (which, because many of the texts are historical narrative sources, are of course not well served by relational structures), but to model some aspects of how the prosopographer thinks about their materials, and their task. The article describes how the presentation of a prosopography in this way benefits the end user as well, allowing access via many potential indices and searches. Finally, it begins an exploration of how a user of our databases might interpret what the database tells them.},
    issn = {0268-1145},
    doi = {10.1093/llc/fqi022},
    url = {https://doi.org/10.1093/llc/fqi022},
    eprint = {https://academic.oup.com/dsh/article-pdf/20/Suppl/3/6272634/fqi022.pdf},
}






@article{Profile-Generation-from-web-sources-an-IE-system--Ranjan-etal-2022,
  author       = {Rishabh Ranjan and
                  H. Vathsala and
                  Shashidhar G. Koolagudi},
  title        = {Profile generation from web sources: an information extraction system},
  journal      = {Soc. Netw. Anal. Min.},
  volume       = {12},
  number       = {1},
  pages        = {2},
  year         = {2022},
  url          = {https://doi.org/10.1007/s13278-021-00827-y},
  doi          = {10.1007/S13278-021-00827-Y},
  timestamp    = {Tue, 21 Dec 2021 17:54:11 +0100},
  biburl       = {https://dblp.org/rec/journals/snam/RanjanVK22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Are-LLMs-good-at-structured-output--Liu-etal-2024,
  author       = {Yu Liu and
                  Duantengchuan Li and
                  Kaili Wang and
                  Zhuoran Xiong and
                  Fobo Shi and
                  Jian Wang and
                  Bing Li and
                  Bo Hang},
  title        = {Are LLMs good at structured outputs? {A} benchmark for evaluating
                  structured output capabilities in LLMs},
  journal      = {Inf. Process. Manag.},
  volume       = {61},
  number       = {5},
  pages        = {103809},
  year         = {2024},
  url          = {https://doi.org/10.1016/j.ipm.2024.103809},
  doi          = {10.1016/J.IPM.2024.103809},
  timestamp    = {Sat, 27 Jul 2024 13:40:54 +0200},
  biburl       = {https://dblp.org/rec/journals/ipm/LiuLWXSWLH24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{LLM-Shots-Best-Fired-System-or-User--Halil-etal-2025,
  author       = {Umut Halil and
                  Jin Huang and
                  Damien Graux and
                  Jeff Z. Pan},
  editor       = {Guodong Long and
                  Michale Blumestein and
                  Yi Chang and
                  Liane Lewin{-}Eytan and
                  Zi Helen Huang and
                  Elad Yom{-}Tov},
  title        = {{LLM} Shots: Best Fired at System or User Prompts?},
  booktitle    = {Companion Proceedings of the {ACM} on Web Conference 2025, {WWW} 2025,
                  Sydney, NSW, Australia, 28 April 2025 - 2 May 2025},
  pages        = {1605--1613},
  publisher    = {{ACM}},
  year         = {2025},
  url          = {https://doi.org/10.1145/3701716.3717814},
  doi          = {10.1145/3701716.3717814},
  timestamp    = {Wed, 11 Jun 2025 21:00:10 +0200},
  biburl       = {https://dblp.org/rec/conf/www/HalilHGP25.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Better-Patching-Using-LLM-Self-Consistency--Ahmed-etal-2023,
  author       = {Toufique Ahmed and
                  Premkumar T. Devanbu},
  title        = {Better Patching Using {LLM} Prompting, via Self-Consistency},
  booktitle    = {38th {IEEE/ACM} International Conference on Automated Software Engineering,
                  {ASE} 2023, Luxembourg, September 11-15, 2023},
  pages        = {1742--1746},
  publisher    = {{IEEE}},
  year         = {2023},
  url          = {https://doi.org/10.1109/ASE56229.2023.00065},
  doi          = {10.1109/ASE56229.2023.00065},
  timestamp    = {Sun, 19 Jan 2025 13:19:17 +0100},
  biburl       = {https://dblp.org/rec/conf/kbse/AhmedD23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Many-shot-ICl--Agarwal-etal-2024,
  author       = {Rishabh Agarwal and
                  Avi Singh and
                  Lei Zhang and
                  Bernd Bohnet and
                  Luis Rosias and
                  Stephanie C. Y. Chan and
                  Biao Zhang and
                  Ankesh Anand and
                  Zaheer Abbas and
                  Azade Nova and
                  John D. Co{-}Reyes and
                  Eric Chu and
                  Feryal M. P. Behbahani and
                  Aleksandra Faust and
                  Hugo Larochelle},
  editor       = {Amir Globersons and
                  Lester Mackey and
                  Danielle Belgrave and
                  Angela Fan and
                  Ulrich Paquet and
                  Jakub M. Tomczak and
                  Cheng Zhang},
  title        = {Many-Shot In-Context Learning},
  booktitle    = {Advances in Neural Information Processing Systems 38: Annual Conference
                  on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver,
                  BC, Canada, December 10 - 15, 2024},
  year         = {2024},
  url          = {http://papers.nips.cc/paper\_files/paper/2024/hash/8cb564df771e9eacbfe9d72bd46a24a9-Abstract-Conference.html},
  timestamp    = {Thu, 13 Feb 2025 16:56:44 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/AgarwalSZBRCZAA24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{GPT-NER-via-LLMs--Wang-etal-2025,
  author       = {Shuhe Wang and
                  Xiaofei Sun and
                  Xiaoya Li and
                  Rongbin Ouyang and
                  Fei Wu and
                  Tianwei Zhang and
                  Jiwei Li and
                  Guoyin Wang and
                  Chen Guo},
  editor       = {Luis Chiruzzo and
                  Alan Ritter and
                  Lu Wang},
  title        = {{GPT-NER:} Named Entity Recognition via Large Language Models},
  booktitle    = {Findings of the Association for Computational Linguistics: {NAACL}
                  2025, Albuquerque, New Mexico, USA, April 29 - May 4, 2025},
  pages        = {4257--4275},
  publisher    = {Association for Computational Linguistics},
  year         = {2025},
  url          = {https://doi.org/10.18653/v1/2025.findings-naacl.239},
  doi          = {10.18653/V1/2025.FINDINGS-NAACL.239},
  timestamp    = {Thu, 14 Aug 2025 11:29:01 +0200},
  biburl       = {https://dblp.org/rec/conf/naacl/WangSLOWZLWG25.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{ULTRA-Unleash-LLMs-for-EAE-Self-Refinement--Zhang-etal-2024,
    title = "{ULTRA}: Unleash {LLM}s' Potential for Event Argument Extraction through Hierarchical Modeling and Pair-wise Self-Refinement",
    author = "Zhang, Xinliang Frederick  and
      Blum, Carter  and
      Choji, Temma  and
      Shah, Shalin  and
      Vempala, Alakananda",
    editor = "Ku, Lun-Wei  and
      Martins, Andre  and
      Srikumar, Vivek",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2024",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.findings-acl.487/",
    doi = "10.18653/v1/2024.findings-acl.487",
    pages = "8172--8185",
    abstract = "Structural extraction of events within discourse is critical since it avails a deeper understanding of communication patterns and behavior trends. Event argument extraction (EAE), at the core of event-centric understanding, is the task of identifying role-specific text spans (i.e., arguments) for a given event. Document-level EAE (DocEAE) focuses on arguments that are scattered across an entire document. In this work, we explore open-source Large Language Models (LLMs) for DocEAE, and propose ULTRA, a hierarchical framework that extracts event arguments more cost-effectively. Further, it alleviates the positional bias issue intrinsic to LLMs. ULTRA sequentially reads text chunks of a document to generate a candidate argument set, upon which non-pertinent candidates are dropped through self-refinement. We introduce LEAFER to address the challenge LLMs face in locating the exact boundary of an argument. ULTRA outperforms strong baselines, including strong supervised models and ChatGPT, by 9.8{\%} when evaluated by Exact Match (EM)."
}


@inproceedings{2iner-instructive-and-ICL-on-NER--Zhang-etal-2023,
    title = "2{INER}: Instructive and In-Context Learning on Few-Shot Named Entity Recognition",
    author = "Zhang, Jiasheng  and
      Liu, Xikai  and
      Lai, Xinyi  and
      Gao, Yan  and
      Wang, Shusen  and
      Hu, Yao  and
      Lin, Yiqing",
    editor = "Bouamor, Houda  and
      Pino, Juan  and
      Bali, Kalika",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2023",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-emnlp.259/",
    doi = "10.18653/v1/2023.findings-emnlp.259",
    pages = "3940--3951",
    abstract = "Prompt-based learning has emerged as a powerful technique in natural language processing (NLP) due to its ability to leverage pre-training knowledge for downstream few-shot tasks. In this paper, we propose 2INER, a novel text-to-text framework for Few-Shot Named Entity Recognition (NER) tasks. Our approach employs instruction finetuning based on InstructionNER to enable the model to effectively comprehend and process task-specific instructions, including both main and auxiliary tasks. We also introduce a new auxiliary task, called Type Extracting, to enhance the model{'}s understanding of entity types in the overall semantic context of a sentence. To facilitate in-context learning, we concatenate examples to the input, enabling the model to learn from additional contextual information. Experimental results on four datasets demonstrate that our approach outperforms existing Few-Shot NER methods and remains competitive with state-of-the-art standard NER algorithms."
}



@inproceedings{Sentence-BERT--Reimers-etal-2019,
  author       = {Nils Reimers and
                  Iryna Gurevych},
  editor       = {Kentaro Inui and
                  Jing Jiang and
                  Vincent Ng and
                  Xiaojun Wan},
  title        = {Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks},
  booktitle    = {Proceedings of the 2019 Conference on Empirical Methods in Natural
                  Language Processing and the 9th International Joint Conference on
                  Natural Language Processing, {EMNLP-IJCNLP} 2019, Hong Kong, China,
                  November 3-7, 2019},
  pages        = {3980--3990},
  publisher    = {Association for Computational Linguistics},
  year         = {2019},
  url          = {https://doi.org/10.18653/v1/D19-1410},
  doi          = {10.18653/V1/D19-1410},
  timestamp    = {Thu, 07 Apr 2022 09:14:07 +0200},
  biburl       = {https://dblp.org/rec/conf/emnlp/ReimersG19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{Evaluation-Measures--Achananuparp-etal-2008,
  author       = {Palakorn Achananuparp and
                  Xiaohua Hu and
                  Xiajiong Shen},
  editor       = {Il{-}Yeol Song and
                  Johann Eder and
                  Tho Manh Nguyen},
  title        = {The Evaluation of Sentence Similarity Measures},
  booktitle    = {Data Warehousing and Knowledge Discovery, 10th International Conference,
                  DaWaK 2008, Turin, Italy, September 2-5, 2008, Proceedings},
  series       = {Lecture Notes in Computer Science},
  volume       = {5182},
  pages        = {305--316},
  publisher    = {Springer},
  year         = {2008},
  url          = {https://doi.org/10.1007/978-3-540-85836-2\_29},
  doi          = {10.1007/978-3-540-85836-2\_29},
  timestamp    = {Fri, 09 Apr 2021 17:11:10 +0200},
  biburl       = {https://dblp.org/rec/conf/dawak/AchananuparpHS08.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{CiteSeer--Giles-etal-1998,
  author       = {C. Lee Giles and
                  Kurt D. Bollacker and
                  Steve Lawrence},
  title        = {CiteSeer: An Automatic Citation Indexing System},
  booktitle    = {Proceedings of the 3rd {ACM} International Conference on Digital Libraries,
                  June 23-26, 1998, Pittsburgh, PA, {USA}},
  pages        = {89--98},
  publisher    = {{ACM}},
  year         = {1998},
  url          = {https://doi.org/10.1145/276675.276685},
  doi          = {10.1145/276675.276685},
  timestamp    = {Sun, 25 Oct 2020 23:16:13 +0100},
  biburl       = {https://dblp.org/rec/conf/dl/GilesBL98.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{GenIE--Josifoski-etal-2022,
  author       = {Martin Josifoski and
                  Nicola De Cao and
                  Maxime Peyrard and
                  Fabio Petroni and
                  Robert West},
  editor       = {Marine Carpuat and
                  Marie{-}Catherine de Marneffe and
                  Iv{\'{a}}n Vladimir Meza Ru{\'{\i}}z},
  title        = {GenIE: Generative Information Extraction},
  booktitle    = {Proceedings of the 2022 Conference of the North American Chapter of
                  the Association for Computational Linguistics: Human Language Technologies,
                  {NAACL} 2022, Seattle, WA, United States, July 10-15, 2022},
  pages        = {4626--4643},
  publisher    = {Association for Computational Linguistics},
  year         = {2022},
  url          = {https://doi.org/10.18653/v1/2022.naacl-main.342},
  doi          = {10.18653/V1/2022.NAACL-MAIN.342},
  timestamp    = {Sun, 02 Oct 2022 16:12:49 +0200},
  biburl       = {https://dblp.org/rec/conf/naacl/JosifoskiCPP022.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}



@article{Structured-IE-from-Scientific-Text-with-LLMs--Dagdelen-etal-2024,
  author    = {John Dagdelen and Alexander Dunn and Sanghoon Lee and Nicholas Walker and Andrew S. Rosen and Gerbrand Ceder and Kristin A. Persson and Anubhav Jain},
  title     = {Structured information extraction from scientific text with large language models},
  journal   = {Nature Communications},
  year      = {2024},
  volume    = {15},
  number    = {1},
  pages     = {1418},
  doi       = {10.1038/s41467-024-45563-x},
  url       = {https://doi.org/10.1038/s41467-024-45563-x},
  issn      = {2041-1723},
  publisher = {Springer Nature}
}



@inproceedings{RE-in-Legal-Domain-Based-on-LLMs--Li-Yi-2024,
author = {Li, Shiye and Yi, Li},
title = {A Few-Shot Entity Relation Extraction Method in the Legal Domain Based on Large Language Models},
year = {2024},
isbn = {9798400717147},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3675417.3675513},
doi = {10.1145/3675417.3675513},
abstract = {With the increasing transparency of judicial information, extracting implicit legal information from a massive corpus of legal documents becomes more academically valuable and practically significant. Large Language Models (LLMs) have demonstrated outstanding performance in many NLP tasks, particularly in generative tasks. However, satisfactory results are often elusive in vertical domains like legal entity relation extraction tasks. Due to the scarcity of well-annotated training data in the legal domain, and the expensive and time-consuming nature of labeling such data, research on few-shot learning becomes particularly crucial. Leveraging the advantage of large models pre-trained on extensive datasets, capable of acquiring vast prior knowledge of various tasks and adapting quickly to new tasks, this paper proposes a few-shot entity relation extraction method in the legal domain based on large language models. The proposed method is evaluated on two publicly available legal entity relation extraction datasets through relevant experiments. The research results indicate that the proposed approach reduces the cost of constructing training data and exhibits excellent performance in few-shot legal entity relation extraction tasks. The F1 score on two public datasets is improved by 2.8\% and 3.1\%, respectively, compared to traditional deep learning models, while maintaining better generalization capabilities.},
booktitle = {Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence},
pages = {580–586},
numpages = {7},
location = {Hongkong, China},
series = {DEAI '24}
}


@inproceedings{APIS-Prosopographical-Information-System--Schlögl-Lejtovicz-2017,
  title={A Prosopographical Information System (APIS).},
  author={Schl{\"o}gl, Matthias and Lejtovicz, Katalin},
  booktitle={BD},
  pages={53--58},
  year={2017}
}


@inproceedings{Harvesting-of-Biographical-Data--Plum-etal-2019,
  author       = {Alistair Plum and
                  Marcos Zampieri and
                  Constantin Orasan and
                  Eveline Wandl{-}Vogt and
                  Ruslan Mitkov},
  editor       = {Angel Daza and
                  Antske Fokkens and
                  Petya Osenova and
                  Kiril Simov and
                  Alexander Popov and
                  Paul Arthur and
                  Thierry Declerck and
                  Ronald Sluijter and
                  Serge ter Braake and
                  Eveline Wandl{-}Vogt},
  title        = {Large-scale Data Harvesting for Biographical Data},
  booktitle    = {Proceedings of the Third Conference on Biographical Data in a Digital
                  World 2019, Varna, Bulgaria, September 5-6, 2019},
  series       = {{CEUR} Workshop Proceedings},
  volume       = {3152},
  pages        = {66--72},
  publisher    = {CEUR-WS.org},
  year         = {2019},
  url          = {https://ceur-ws.org/Vol-3152/BD2019\_paper\_9.pdf},
  timestamp    = {Fri, 10 Mar 2023 16:23:33 +0100},
  biburl       = {https://dblp.org/rec/conf/bd/PlumZOWM19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@article{Scalable-IE-from-electronic-health-records-using-LLMs--Gu-etal-2025,
  author    = {Gu, Bowen and Shao, Vivian and Liao, Ziqian and Carducci, Valentina and Brufau, Santiago Romero and Yang, Jie and Desai, Rishi J.},
  title     = {Scalable information extraction from free text electronic health records using large language models},
  journal   = {BMC Medical Research Methodology},
  year      = {2025},
  volume    = {25},
  number    = {1},
  pages     = {23},
  doi       = {10.1186/s12874-025-02470-z},
  url       = {https://doi.org/10.1186/s12874-025-02470-z},
  issn      = {1471-2288}
}


@incollection{kreutel2023forschungsplattform,
  author    = {Kreutel, J{\"o}rn and M{\"o}bius, Thomas and Dahlke, Birgit and Martus, Steffen},
  title     = {Forschungsplattform Literarisches Feld DDR: Ein Werkstattbericht zur prosopographischen Erfassung von Schriftstellerinnen in der DDR},
  booktitle = {Historische Biographik und kritische Prosopographie als Instrumente in den Geschichtswissenschaften},
  editor    = {Albrecht, Helmuth and Farrenkopf, Michael and Maier, Helmut and Meyer, Torsten},
  address   = {Berlin, Boston},
  publisher = {De Gruyter Oldenbourg},
  year      = {2023},
  pages     = {141--166},
  doi       = {10.1515/9783111137063-008}
}



@book{bourdieu1992regles,
  title={Les r{\`e}gles de l'art : gen{\`e}se et structure du champ litt{\'e}raire},
  author={Bourdieu, Pierre},
  year={1992},
  address={Paris},
  publisher={Éditions du Seuil},
  pages={480}
}

@article{hallucinations-in-llms--lei-etal-2025,
author = {Huang, Lei and Yu, Weijiang and Ma, Weitao and Zhong, Weihong and Feng, Zhangyin and Wang, Haotian and Chen, Qianglong and Peng, Weihua and Feng, Xiaocheng and Qin, Bing and Liu, Ting},
title = {A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions},
year = {2025},
issue_date = {March 2025},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {43},
number = {2},
issn = {1046-8188},
url = {https://doi.org/10.1145/3703155},
doi = {10.1145/3703155},
abstract = {The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition. Nevertheless, LLMs are prone to hallucination, generating plausible yet nonfactual content. This phenomenon raises significant concerns over the reliability of LLMs in real-world information retrieval (IR) systems and has attracted intensive research to detect and mitigate such hallucinations. Given the open-ended general-purpose attributes inherent to LLMs, LLM hallucinations present distinct challenges that diverge from prior task-specific models. This divergence highlights the urgency for a nuanced understanding and comprehensive overview of recent advances in LLM hallucinations. In this survey, we begin with an innovative taxonomy of hallucination in the era of LLM and then delve into the factors contributing to hallucinations. Subsequently, we present a thorough overview of hallucination detection methods and benchmarks. Our discussion then transfers to representative methodologies for mitigating LLM hallucinations. Additionally, we delve into the current limitations faced by retrieval-augmented LLMs in combating hallucinations, offering insights for developing more robust IR systems. Finally, we highlight the promising research directions on LLM hallucinations, including hallucination in large vision-language models and understanding of knowledge boundaries in LLM hallucinations.},
journal = {ACM Trans. Inf. Syst.},
month = jan,
articleno = {42},
numpages = {55},
keywords = {Large Language Models, Hallucination, Factuality, Faithfulness}
}


@software{Baccianella_JSON_Repair_-_2025,
    author  = "Stefano {Baccianella}",
    month   = "feb",
    title   = "JSON Repair - A python module to repair invalid JSON, commonly used to parse the output of LLMs",
    url     = "https://github.com/mangiucugna/json_repair",
    version = "0.39.1",
    year    = 2025
}


@inproceedings{Self-Refine-Iterative-refinement-with-self-feedback--Madaan-etal-2023,
  author       = {Aman Madaan and
                  Niket Tandon and
                  Prakhar Gupta and
                  Skyler Hallinan and
                  Luyu Gao and
                  Sarah Wiegreffe and
                  Uri Alon and
                  Nouha Dziri and
                  Shrimai Prabhumoye and
                  Yiming Yang and
                  Shashank Gupta and
                  Bodhisattwa Prasad Majumder and
                  Katherine Hermann and
                  Sean Welleck and
                  Amir Yazdanbakhsh and
                  Peter Clark},
  editor       = {Alice Oh and
                  Tristan Naumann and
                  Amir Globerson and
                  Kate Saenko and
                  Moritz Hardt and
                  Sergey Levine},
  title        = {Self-Refine: Iterative Refinement with Self- Feedback},
  booktitle    = {Advances in Neural Information Processing Systems 36: Annual Conference
                  on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans,
                  LA, USA, December 10 - 16, 2023},
  year         = {2023},
  url          = {http://papers.nips.cc/paper\_files/paper/2023/hash/91edff07232fb1b55a505a9e9f6c0ff3-Abstract-Conference.html},
  timestamp    = {Fri, 01 Mar 2024 16:26:20 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/MadaanTGHGW0DPY23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{ProgGEN-Generating-NER-Datasets--Heng-etal-2024,
  author       = {Yuzhao Heng and
                  Chunyuan Deng and
                  Yitong Li and
                  Yue Yu and
                  Yinghao Li and
                  Rongzhi Zhang and
                  Chao Zhang},
  editor       = {Lun{-}Wei Ku and
                  Andre Martins and
                  Vivek Srikumar},
  title        = {ProgGen: Generating Named Entity Recognition Datasets Step-by-step
                  with Self-Reflexive Large Language Models},
  booktitle    = {Findings of the Association for Computational Linguistics, {ACL} 2024,
                  Bangkok, Thailand and virtual meeting, August 11-16, 2024},
  pages        = {15992--16030},
  publisher    = {Association for Computational Linguistics},
  year         = {2024},
  url          = {https://doi.org/10.18653/v1/2024.findings-acl.947},
  doi          = {10.18653/V1/2024.FINDINGS-ACL.947},
  timestamp    = {Thu, 14 Nov 2024 15:14:17 +0100},
  biburl       = {https://dblp.org/rec/conf/acl/HengDLYLZZ24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{Zero-shot-temproal-RE-with-ChatGPT--Yuan-etal-2023,
  author       = {Chenhan Yuan and
                  Qianqian Xie and
                  Sophia Ananiadou},
  editor       = {Dina Demner{-}Fushman and
                  Sophia Ananiadou and
                  Kevin Cohen},
  title        = {Zero-shot Temporal Relation Extraction with ChatGPT},
  booktitle    = {The 22nd Workshop on Biomedical Natural Language Processing and BioNLP
                  Shared Tasks, BioNLP@ACL 2023, Toronto, Canada, 13 July 2023},
  pages        = {92--102},
  publisher    = {Association for Computational Linguistics},
  year         = {2023},
  url          = {https://doi.org/10.18653/v1/2023.bionlp-1.7},
  doi          = {10.18653/V1/2023.BIONLP-1.7},
  timestamp    = {Sun, 19 Jan 2025 13:40:41 +0100},
  biburl       = {https://dblp.org/rec/conf/bionlp/YuanXA23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{PromptNER-Prompt-Locating-and-Typing-for-NER--Shen-etal-2023,
  author       = {Yongliang Shen and
                  Zeqi Tan and
                  Shuhui Wu and
                  Wenqi Zhang and
                  Rongsheng Zhang and
                  Yadong Xi and
                  Weiming Lu and
                  Yueting Zhuang},
  editor       = {Anna Rogers and
                  Jordan L. Boyd{-}Graber and
                  Naoaki Okazaki},
  title        = {PromptNER: Prompt Locating and Typing for Named Entity Recognition},
  booktitle    = {Proceedings of the 61st Annual Meeting of the Association for Computational
                  Linguistics (Volume 1: Long Papers), {ACL} 2023, Toronto, Canada,
                  July 9-14, 2023},
  pages        = {12492--12507},
  publisher    = {Association for Computational Linguistics},
  year         = {2023},
  url          = {https://doi.org/10.18653/v1/2023.acl-long.698},
  doi          = {10.18653/V1/2023.ACL-LONG.698},
  timestamp    = {Mon, 30 Jun 2025 11:58:49 +0200},
  biburl       = {https://dblp.org/rec/conf/acl/0001TWZZX0Z23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{BioCRM-Data-Model--Tuominen-etal-2017,
  author       = {Jouni Tuominen and
                  Eero Hyv{\"{o}}nen and
                  Petri Leskinen},
  editor       = {Antske Fokkens and
                  Serge ter Braake and
                  Ronald Sluijter and
                  Paul Longley Arthur and
                  Eveline Wandl{-}Vogt},
  title        = {Bio {CRM:} {A} Data Model for Representing Biographical Data for Prosopographical
                  Research},
  booktitle    = {Proceedings of the Second Conference on Biographical Data in a Digital
                  World 2017, Linz, Austria, November 6-7, 2017},
  series       = {{CEUR} Workshop Proceedings},
  volume       = {2119},
  pages        = {59--66},
  publisher    = {CEUR-WS.org},
  year         = {2017},
  url          = {https://ceur-ws.org/Vol-2119/paper10.pdf},
  timestamp    = {Fri, 10 Mar 2023 16:23:33 +0100},
  biburl       = {https://dblp.org/rec/conf/bd/TuominenHL17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{IE-Distilling-structured-from-unstructured--McCallum-2005,
  author       = {Andrew McCallum},
  title        = {Information extraction: distilling structured data from unstructured
                  text},
  journal      = {{ACM} Queue},
  volume       = {3},
  number       = {9},
  pages        = {48--57},
  year         = {2005},
  url          = {https://doi.org/10.1145/1105664.1105679},
  doi          = {10.1145/1105664.1105679},
  timestamp    = {Mon, 28 Aug 2023 21:37:15 +0200},
  biburl       = {https://dblp.org/rec/journals/queue/McCallum05.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}




@inproceedings{LLMs-are-zero-shot-reasoners--Kojima-etal-2022,
 author = {Kojima, Takeshi and Gu, Shixiang (Shane) and Reid, Machel and Matsuo, Yutaka and Iwasawa, Yusuke},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
 pages = {22199--22213},
 publisher = {Curran Associates, Inc.},
 title = {Large Language Models are Zero-Shot Reasoners},
 url = {https://proceedings.neurips.cc/paper_files/paper/2022/file/8bb0d291acd4acf06ef112099c16f326-Paper-Conference.pdf},
 volume = {35},
 year = {2022}
}


@article{genealogy-of-DH--Dalbello-etal-2011,
  author       = {Marija Dalbello},
  title        = {A genealogy of digital humanities},
  journal      = {J. Documentation},
  volume       = {67},
  number       = {3},
  pages        = {480--506},
  year         = {2011},
  url          = {https://doi.org/10.1108/00220411111124550},
  doi          = {10.1108/00220411111124550},
  timestamp    = {Sun, 06 Sep 2020 16:56:28 +0200},
  biburl       = {https://dblp.org/rec/journals/jd/Dalbello11.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{CoT-elicits-reasoning-in-LLMs--Google-brain-team-2022,
  author       = {Jason Wei and
                  Xuezhi Wang and
                  Dale Schuurmans and
                  Maarten Bosma and
                  Brian Ichter and
                  Fei Xia and
                  Ed H. Chi and
                  Quoc V. Le and
                  Denny Zhou},
  editor       = {Sanmi Koyejo and
                  S. Mohamed and
                  A. Agarwal and
                  Danielle Belgrave and
                  K. Cho and
                  A. Oh},
  title        = {Chain-of-Thought Prompting Elicits Reasoning in Large Language Models},
  booktitle    = {Advances in Neural Information Processing Systems 35: Annual Conference
                  on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans,
                  LA, USA, November 28 - December 9, 2022},
  year         = {2022},
  url          = {http://papers.nips.cc/paper\_files/paper/2022/hash/9d5609613524ecf4f15af0f7b31abca4-Abstract-Conference.html},
  timestamp    = {Tue, 12 Nov 2024 16:50:49 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/Wei0SBIXCLZ22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Extract-accurate-data-PE--Polak-2024,
  author       = {Maciej P. Polak and
                  Dane Morgan},
  title        = {Extracting Accurate Materials Data from Research Papers with Conversational
                  Language Models and Prompt Engineering - Example of ChatGPT},
  journal      = {CoRR},
  volume       = {abs/2303.05352},
  year         = {2023},
  url          = {https://doi.org/10.48550/arXiv.2303.05352},
  doi          = {10.48550/ARXIV.2303.05352},
  eprinttype    = {arXiv},
  eprint       = {2303.05352},
  timestamp    = {Mon, 05 Feb 2024 20:18:29 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2303-05352.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Deliberate-then-generate-PE--Wang-2023,
  author       = {Bei Li and
                  Rui Wang and
                  Junliang Guo and
                  Kaitao Song and
                  Xu Tan and
                  Hany Hassan and
                  Arul Menezes and
                  Tong Xiao and
                  Jiang Bian and
                  JingBo Zhu},
  title        = {Deliberate then Generate: Enhanced Prompting Framework for Text Generation},
  journal      = {CoRR},
  volume       = {abs/2305.19835},
  year         = {2023},
  url          = {https://doi.org/10.48550/arXiv.2305.19835},
  doi          = {10.48550/ARXIV.2305.19835},
  eprinttype    = {arXiv},
  eprint       = {2305.19835},
  timestamp    = {Tue, 05 Dec 2023 20:52:43 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2305-19835.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{LMs-are-few-shot-learners--Brown-2020,
  author       = {Tom B. Brown and
                  Benjamin Mann and
                  Nick Ryder and
                  Melanie Subbiah and
                  Jared Kaplan and
                  Prafulla Dhariwal and
                  Arvind Neelakantan and
                  Pranav Shyam and
                  Girish Sastry and
                  Amanda Askell and
                  Sandhini Agarwal and
                  Ariel Herbert{-}Voss and
                  Gretchen Krueger and
                  Tom Henighan and
                  Rewon Child and
                  Aditya Ramesh and
                  Daniel M. Ziegler and
                  Jeffrey Wu and
                  Clemens Winter and
                  Christopher Hesse and
                  Mark Chen and
                  Eric Sigler and
                  Mateusz Litwin and
                  Scott Gray and
                  Benjamin Chess and
                  Jack Clark and
                  Christopher Berner and
                  Sam McCandlish and
                  Alec Radford and
                  Ilya Sutskever and
                  Dario Amodei},
  editor       = {Hugo Larochelle and
                  Marc'Aurelio Ranzato and
                  Raia Hadsell and
                  Maria{-}Florina Balcan and
                  Hsuan{-}Tien Lin},
  title        = {Language Models are Few-Shot Learners},
  booktitle    = {Advances in Neural Information Processing Systems 33: Annual Conference
                  on Neural Information Processing Systems 2020, NeurIPS 2020, December
                  6-12, 2020, virtual},
  year         = {2020},
  url          = {https://proceedings.neurips.cc/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html},
  timestamp    = {Thu, 25 May 2023 10:38:31 +0200},
  biburl       = {https://dblp.org/rec/conf/nips/BrownMRSKDNSSAA20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}



@article{Testing-PE-Methods-Gen-KE--Polat-2024,
  title={Testing prompt engineering methods for knowledge extraction from text},
  author={Fina Polat and Ilaria Tiddi and Paul Groth},
  journal={Semantic Web},
  doi = {10.3233/SW-243719},
  type = {Article},
  year={2024},
  url={https://www.semantic-web-journal.net/system/files/swj3719.pdf}
}

@article{LLAMA--Touvron-2023,
  author       = {Hugo Touvron and
                  Thibaut Lavril and
                  Gautier Izacard and
                  Xavier Martinet and
                  Marie{-}Anne Lachaux and
                  Timoth{\'{e}}e Lacroix and
                  Baptiste Rozi{\`{e}}re and
                  Naman Goyal and
                  Eric Hambro and
                  Faisal Azhar and
                  Aur{\'{e}}lien Rodriguez and
                  Armand Joulin and
                  Edouard Grave and
                  Guillaume Lample},
  title        = {LLaMA: Open and Efficient Foundation Language Models},
  journal      = {CoRR},
  volume       = {abs/2302.13971},
  year         = {2023},
  url          = {https://ai.meta.com/research/publications/llama-open-and-efficient-foundation-language-models/},
  eprint       = {2302.13971},
  timestamp    = {Tue, 11 Feb 2025 12:43:02 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2302-13971.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@article{ChatGPTs-IE-performance--Li-2023,
  title={Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness},
  author={Bo Li and Gexiang Fang and Yang Yang and Quansen Wang and Wei Ye and Wen Zhao and Shikun Zhang},
  journal={ArXiv},
  year={2023},
  volume={abs/2304.11633},
  url={https://api.semanticscholar.org/CorpusID:258297899}
}


@article{Transformers-in-healthcare--Denecke-2024,
  author       = {Kerstin Denecke and
                  Richard May and
                  Octavio Rivera Romero},
  title        = {Transformer Models in Healthcare: {A} Survey and Thematic Analysis
                  of Potentials, Shortcomings and Risks},
  journal      = {J. Medical Syst.},
  volume       = {48},
  number       = {1},
  pages        = {23},
  year         = {2024},
  url          = {https://doi.org/10.1007/s10916-024-02043-5},
  doi          = {10.1007/S10916-024-02043-5},
  timestamp    = {Fri, 08 Mar 2024 13:22:04 +0100},
  biburl       = {https://dblp.org/rec/journals/jms/DeneckeMR24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{LLMs-accelarate-annotation-for-medical-IE--Google-Research-2023,
  author       = {Akshay Goel and
                  Almog Gueta and
                  Omry Gilon and
                  Chang Liu and
                  Sofia Erell and
                  Lan Huong Nguyen and
                  Xiaohong Hao and
                  Bolous Jaber and
                  Shashir Reddy and
                  Rupesh Kartha and
                  Jean Steiner and
                  Itay Laish and
                  Amir Feder},
  editor       = {Stefan Hegselmann and
                  Antonio Parziale and
                  Divya Shanmugam and
                  Shengpu Tang and
                  Mercy Nyamewaa Asiedu and
                  Serina Chang and
                  Tom Hartvigsen and
                  Harvineet Singh},
  title        = {LLMs Accelerate Annotation for Medical Information Extraction},
  booktitle    = {Machine Learning for Health, ML4H@NeurIPS 2023, 10 December 2023,
                  New Orleans, Louisiana, {USA}},
  series       = {Proceedings of Machine Learning Research},
  volume       = {225},
  pages        = {82--100},
  publisher    = {{PMLR}},
  year         = {2023},
  url          = {https://proceedings.mlr.press/v225/goel23a.html},
  timestamp    = {Tue, 20 Feb 2024 17:19:52 +0100},
  biburl       = {https://dblp.org/rec/conf/ml4h/GoelGGLENHJRKSL23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{LLMs-for-GenIE-Survey--Xu-2024,
  author       = {Derong Xu and
                  Wei Chen and
                  Wenjun Peng and
                  Chao Zhang and
                  Tong Xu and
                  Xiangyu Zhao and
                  Xian Wu and
                  Yefeng Zheng and
                  Yang Wang and
                  Enhong Chen},
  title        = {Large language models for generative information extraction: a survey},
  journal      = {Frontiers Comput. Sci.},
  volume       = {18},
  number       = {6},
  pages        = {186357},
  year         = {2024},
  url          = {https://doi.org/10.1007/s11704-024-40555-y},
  doi          = {10.1007/S11704-024-40555-Y},
  timestamp    = {Mon, 03 Mar 2025 21:38:51 +0100},
  biburl       = {https://dblp.org/rec/journals/fcsc/XuCPZXZWZWC24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}



@article{Improving-LLMs-for-clinical-NER-via-PE,
  author       = {Yan Hu and
                  Qingyu Chen and
                  Jingcheng Du and
                  Xueqing Peng and
                  Vipina Kuttichi Keloth and
                  Xu Zuo and
                  Yujia Zhou and
                  Zehan Li and
                  Xiaoqian Jiang and
                  Zhiyong Lu and
                  Kirk Roberts and
                  Hua Xu},
  title        = {Improving large language models for clinical named entity recognition
                  via prompt engineering},
  journal      = {J. Am. Medical Informatics Assoc.},
  volume       = {31},
  number       = {9},
  pages        = {1812--1820},
  year         = {2024},
  url          = {https://doi.org/10.1093/jamia/ocad259},
  doi          = {10.1093/JAMIA/OCAD259},
  timestamp    = {Mon, 30 Sep 2024 07:54:36 +0200},
  biburl       = {https://dblp.org/rec/journals/jamia/HuCDPKZZLJLRX24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Deep-Learning-for-NER--Hou-2024,
  author       = {Zhentao Hu and
                  Wei Hou and
                  Xianxing Liu},
  title        = {Deep learning for named entity recognition: a survey},
  journal      = {Neural Comput. Appl.},
  volume       = {36},
  number       = {16},
  pages        = {8995--9022},
  year         = {2024},
  url          = {https://doi.org/10.1007/s00521-024-09646-6},
  doi          = {10.1007/S00521-024-09646-6},
  timestamp    = {Fri, 31 May 2024 21:05:54 +0200},
  biburl       = {https://dblp.org/rec/journals/nca/HuHL24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{ToNER-type-oriented-NER--jiang-2024,
    title = "{T}o{NER}: Type-oriented Named Entity Recognition with Generative Language Model",
    author = "Jiang, Guochao  and
      Luo, Ziqin  and
      Shi, Yuchen  and
      Wang, Dixuan  and
      Liang, Jiaqing  and
      Yang, Deqing",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.1412/",
    pages = "16251--16262",
    abstract = "In recent years, the fine-tuned generative models have been proven more powerful than the previous tagging-based or span-based models on named entity recognition (NER) task. It has also been found that the information related to entities, such as entity types, can prompt a model to achieve NER better. However, it is not easy to determine the entity types indeed existing in the given sentence in advance, and inputting too many potential entity types would distract the model inevitably. To exploit entity types' merit on promoting NER task, in this paper we propose a novel NER framework, namely ToNER based on a generative model. In ToNER, a type matching model is proposed at first to identify the entity types most likely to appear in the sentence. Then, we append a multiple binary classification task to fine-tune the generative model`s encoder, so as to generate the refined representation of the input sentence. Moreover, we add an auxiliary task for the model to discover the entity types which further fine-tunes the model to output more accurate results. Our extensive experiments on some NER benchmarks verify the effectiveness of our proposed strategies in ToNER that are oriented towards entity types' exploitation."
}

@inproceedings{Self-improving-for-NER-with-LLMs--Xie-2024,
  author       = {Tingyu Xie and
                  Qi Li and
                  Yan Zhang and
                  Zuozhu Liu and
                  Hongwei Wang},
  editor       = {Kevin Duh and
                  Helena G{\'{o}}mez{-}Adorno and
                  Steven Bethard},
  title        = {Self-Improving for Zero-Shot Named Entity Recognition with Large Language
                  Models},
  booktitle    = {Proceedings of the 2024 Conference of the North American Chapter of
                  the Association for Computational Linguistics: Human Language Technologies:
                  Short Papers, {NAACL} 2024, Mexico City, Mexico, June 16-21, 2024},
  pages        = {583--593},
  publisher    = {Association for Computational Linguistics},
  year         = {2024},
  url          = {https://doi.org/10.18653/v1/2024.naacl-short.49},
  doi          = {10.18653/V1/2024.NAACL-SHORT.49},
  timestamp    = {Mon, 30 Sep 2024 07:54:34 +0200},
  biburl       = {https://dblp.org/rec/conf/naacl/XieLZLW24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Self-consistency-improves-CoT-in-LMs--Wang-2023,
  author       = {Xuezhi Wang and
                  Jason Wei and
                  Dale Schuurmans and
                  Quoc V. Le and
                  Ed H. Chi and
                  Sharan Narang and
                  Aakanksha Chowdhery and
                  Denny Zhou},
  title        = {Self-Consistency Improves Chain of Thought Reasoning in Language Models},
  booktitle    = {The Eleventh International Conference on Learning Representations,
                  {ICLR} 2023, Kigali, Rwanda, May 1-5, 2023},
  publisher    = {OpenReview.net},
  year         = {2023},
  url          = {https://openreview.net/forum?id=1PL1NIMMrw},
  timestamp    = {Wed, 24 Jul 2024 16:50:33 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/0002WSLCNCZ23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}



@inproceedings{Evaluating-GenLMs-in-IE--Fan-2024,
  author       = {Yuchen Fan and
                  Yantao Liu and
                  Zijun Yao and
                  Jifan Yu and
                  Lei Hou and
                  Juanzi Li},
  editor       = {Nicoletta Calzolari and
                  Min{-}Yen Kan and
                  V{\'{e}}ronique Hoste and
                  Alessandro Lenci and
                  Sakriani Sakti and
                  Nianwen Xue},
  title        = {Evaluating Generative Language Models in Information Extraction as
                  Subjective Question Correction},
  booktitle    = {Proceedings of the 2024 Joint International Conference on Computational
                  Linguistics, Language Resources and Evaluation, {LREC/COLING} 2024,
                  20-25 May, 2024, Torino, Italy},
  pages        = {6409--6417},
  publisher    = {{ELRA} and {ICCL}},
  year         = {2024},
  url          = {https://aclanthology.org/2024.lrec-main.567},
  timestamp    = {Wed, 12 Jun 2024 21:04:47 +0200},
  biburl       = {https://dblp.org/rec/conf/coling/FanL0YHL24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@misc{hugging-face-leaderboard,
  author = {Clémentine Fourrier and Nathan Habib and Alina Lozovskaya and Konrad Szafer and Thomas Wolf},
  title = {Open LLM Leaderboard v2},
  year = {2024},
  publisher = {Hugging Face},
  howpublished = "\url{https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard}",
}

@misc{IFEval-eval-framework-zhou-2023,
  title={Instruction-Following Evaluation for Large Language Models},
  author={Jeffrey Zhou and Tianjian Lu and Swaroop Mishra and Siddhartha Brahma and Sujoy Basu and Yi Luan and Denny Zhou and Le Hou},
  year={2023},
  eprint={2311.07911},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2311.07911},
}

@inproceedings{MMLU-Pro-eval-framework-wang-2024,
  author       = {Yubo Wang and
                  Xueguang Ma and
                  Ge Zhang and
                  Yuansheng Ni and
                  Abhranil Chandra and
                  Shiguang Guo and
                  Weiming Ren and
                  Aaran Arulraj and
                  Xuan He and
                  Ziyan Jiang and
                  Tianle Li and
                  Max Ku and
                  Kai Wang and
                  Alex Zhuang and
                  Rongqi Fan and
                  Xiang Yue and
                  Wenhu Chen},
  editor       = {Amir Globersons and
                  Lester Mackey and
                  Danielle Belgrave and
                  Angela Fan and
                  Ulrich Paquet and
                  Jakub M. Tomczak and
                  Cheng Zhang},
  title        = {MMLU-Pro: {A} More Robust and Challenging Multi-Task Language Understanding
                  Benchmark},
  booktitle    = {Advances in Neural Information Processing Systems 38: Annual Conference
                  on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver,
                  BC, Canada, December 10 - 15, 2024},
  year         = {2024},
  url          = {http://papers.nips.cc/paper\_files/paper/2024/hash/ad236edc564f3e3156e1b2feafb99a24-Abstract-Datasets\_and\_Benchmarks\_Track.html},
  timestamp    = {Thu, 13 Feb 2025 16:56:44 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/WangMZNCGRAHJLK24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{MuSR-eval-framework--sprague-2024,
  author       = {Zayne Sprague and
                  Xi Ye and
                  Kaj Bostrom and
                  Swarat Chaudhuri and
                  Greg Durrett},
  title        = {MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning},
  booktitle    = {The Twelfth International Conference on Learning Representations,
                  {ICLR} 2024, Vienna, Austria, May 7-11, 2024},
  publisher    = {OpenReview.net},
  year         = {2024},
  url          = {https://openreview.net/forum?id=jenyYQzue1},
  timestamp    = {Mon, 29 Jul 2024 17:17:48 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/SpragueYBCD24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@misc{BBH-eval-framework--suzgun-2022,
  title={Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them},
  author={Mirac Suzgun and Nathan Scales and Nathanael Schärli and Sebastian Gehrmann and Yi Tay and Hyung Won Chung and Aakanksha Chowdhery and Quoc V. Le and Ed H. Chi and Denny Zhou and Jason Wei},
  year={2022},
  eprint={2210.09261},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2210.09261},
}

@inproceedings{MATH-eval-framework--hendrycks-2021,
  author       = {Dan Hendrycks and
                  Collin Burns and
                  Saurav Kadavath and
                  Akul Arora and
                  Steven Basart and
                  Eric Tang and
                  Dawn Song and
                  Jacob Steinhardt},
  editor       = {Joaquin Vanschoren and
                  Sai{-}Kit Yeung},
  title        = {Measuring Mathematical Problem Solving With the {MATH} Dataset},
  booktitle    = {Proceedings of the Neural Information Processing Systems Track on
                  Datasets and Benchmarks 1, NeurIPS Datasets and Benchmarks 2021, December
                  2021, virtual},
  year         = {2021},
  url          = {https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/be83ab3ecd0db773eb2dc1b0a17836a1-Abstract-round2.html},
  timestamp    = {Thu, 05 May 2022 16:53:59 +0200},
  biburl       = {https://dblp.org/rec/conf/nips/HendrycksBKABTS21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@article{GPQA-eval-framework--rein-2023,
  author       = {David Rein and
                  Betty Li Hou and
                  Asa Cooper Stickland and
                  Jackson Petty and
                  Richard Yuanzhe Pang and
                  Julien Dirani and
                  Julian Michael and
                  Samuel R. Bowman},
  title        = {{GPQA:} {A} Graduate-Level Google-Proof Q{\&}A Benchmark},
  journal      = {CoRR},
  volume       = {abs/2311.12022},
  year         = {2023},
  url          = {https://doi.org/10.48550/arXiv.2311.12022},
  doi          = {10.48550/ARXIV.2311.12022},
  eprinttype    = {arXiv},
  eprint       = {2311.12022},
  timestamp    = {Sun, 19 Jan 2025 13:42:21 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2311-12022.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}





@book{Aho:72,
    author  = {Alfred V. Aho and Jeffrey D. Ullman},
    title   = {The Theory of Parsing, Translation and Compiling},
    year    = "1972",
    volume  = "1",
    publisher = {Prentice-Hall},
    address = {Englewood Cliffs, NJ}
}

@book{APA:83,
    author  = {{American Psychological Association}},
    title   = {Publications Manual},
    year    = "1983",
    publisher = {American Psychological Association},
    address = {Washington, DC}
}

@article{Chandra:81,
	author = {Ashok K. Chandra and Dexter C. Kozen and Larry J. Stockmeyer},
	year = "1981",
	title = {Alternation},
	journal = {Journal of the Association for Computing Machinery},
	volume = "28",
	number = "1",
	pages = "114--133",
	doi = "10.1145/322234.322243",
}

@inproceedings{andrew2007scalable,
  title={Scalable training of {L1}-regularized log-linear models},
  author={Andrew, Galen and Gao, Jianfeng},
  booktitle={Proceedings of the 24th International Conference on Machine Learning},
  pages={33--40},
  year={2007},
}

@book{Gusfield:97,
    author  = {Dan Gusfield},
    title   = {Algorithms on Strings, Trees and Sequences},
    year    = "1997",
    publisher = {Cambridge University Press},
    address = {Cambridge, UK}
}

@article{rasooli-tetrault-2015,
    author    = {Mohammad Sadegh Rasooli and Joel R. Tetreault},
    title     = {Yara Parser: {A} Fast and Accurate Dependency Parser},
    journal   = {Computing Research Repository},
    volume    = {arXiv:1503.06733},
    year      = {2015},
    url       = {http://arxiv.org/abs/1503.06733},
    note    = {version 2}
}

@article{Ando2005,
	Acmid = {1194905},
	Author = {Ando, Rie Kubota and Zhang, Tong},
	Issn = {1532-4435},
	Issue_Date = {12/1/2005},
	Journal = {Journal of Machine Learning Research},
	Month = dec,
	Numpages = {37},
	Pages = {1817--1853},
	Publisher = {JMLR.org},
	Title = {A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data},
	Volume = {6},
	Year = {2005}
}

@book{bourdieu_feld,
  title={Les r{\`e}gles de l'art: gen{\`e}se et structure du champ litt{\'e}raire},
  author={Bourdieu, Pierre},
  publisher={Editions du Seuil},
  address={Paris},
  year={1992}
}

@book{biban,
editor={{Berlin-Brandenburgische Akademie der Wissenschaften}}, 
title={{Literatur in der SBZ/DDR. Bibliographische Annalen 1945-1990.}},
address= {Berlin, Boston},
publisher={de Gruyter Akademie Forschung},
year={2021}
}

@INCOLLECTION{flfddr_werkstattbericht,
 author = {J\"{o}rn Kreutel and Thomas M\"{o}bius and Birgit Dahlke and Steffen Martus},
 title = {{Forschungsplattform Literarisches Feld DDR -- Ein Werkstattbericht zur prosopographischen Erfassung von Schriftsteller:innen in der DDR}},
 publisher = {De Gruyter},
 pages = {141 - 165},
 address = "",
 editor = {Albrecht, Helmuth  and Farrenkopf, Michael  and Maier,  Helmut and Meyer, Torsten},
 booktitle = {Historische Biographik und kritische Prosopographie als Instrumente in den Geschichtswissenschaften},
 year = {2023}
} 
