% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").
@article{radford2019language,
  title={Language models are unsupervised multitask learners},
  author={Radford, Alec and Wu, Jeffrey and Child, Rewon and Luan, David and Amodei, Dario and Sutskever, Ilya and others},
  journal={OpenAI blog},
  volume={1},
  number={8},
  pages={9},
  year={2019}
}

@article{Ji_2023,
   title={Survey of Hallucination in Natural Language Generation},
   author={Ji, Ziwei and Lee, Nayeon and Frieske, Rita and Yu, Tiezheng and Su, Dan and Xu, Yan and Ishii, Etsuko and Bang, Ye Jin and Madotto, Andrea and Fung, Pascale},
   ISSN={1557-7341},
   journal={ACM Computing Surveys},
   publisher={Association for Computing Machinery (ACM)},
   year={2023},
   month=mar,
   volume={55},
   number={12},
   pages={1–38},
   doi={10.1145/3571730},
   url={http://dx.doi.org/10.1145/3571730},
   }

@inproceedings{li-etal-2023-halueval,
    title = "{H}alu{E}val: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models",
    author = "Li, Junyi  and Cheng, Xiaoxue  and Zhao, Xin  and Nie, Jian-Yun  and Wen, Ji-Rong",
    editor = "Bouamor, Houda  and Pino, Juan  and Bali, Kalika",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.emnlp-main.397",
    doi = "10.18653/v1/2023.emnlp-main.397",
    pages = "6449--6464",
}

@misc{friel2023chainpoll,
      title={Chainpoll: A high efficacy method for LLM hallucination detection}, 
      author={Robert Friel and Atindriyo Sanyal},
      year={2023},
      eprint={2310.18344},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@inproceedings{mickus-etal-2024-semeval,
    title = "{S}em{E}val-2024 {T}ask 6: {SHROOM}, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakes",
    author = "Mickus, Timothee and Zosa, Elaine and V{\'a}zquez, Ra{\'u}l and Vahtola, Teemu and Tiedemann, J{\"o}rg and Segonne, Vincent and Raganato, Alessandro and Apidianaki, Marianna",
    booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
}

@article{gekhman2023trueteacher,
  title={Trueteacher: Learning factual consistency evaluation with large language models},
  author={Gekhman, Zorik and Herzig, Jonathan and Aharoni, Roee and Elkind, Chen and Szpektor, Idan},
  journal={arXiv preprint arXiv:2305.11171},
  year={2023}
}

@article{manakul2023selfcheckgpt,
    title={Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models},
    author={Manakul, Potsawee and Liusie, Adian and Gales, Mark JF},
    journal={arXiv preprint arXiv:2303.08896},
    year={2023},
    doi={10.48550/arXiv.2303.08896},
}

@article{liu2019roberta,
    title = {RoBERTa: A Robustly Optimized BERT Pretraining Approach},
    author = {Yinhan Liu and Myle Ott and Naman Goyal and Jingfei Du and Mandar Joshi and Danqi Chen and Omer Levy and Mike Lewis and Luke Zettlemoyer and Veselin Stoyanov},
    journal={arXiv preprint arXiv:1907.11692},
    year = {2019},
    doi = {10.48550/arXiv.1907.11692},
}

@inproceedings{honovich-etal-2022-true-evaluating,
    title = "{TRUE}: Re-evaluating Factual Consistency Evaluation",
    author = "Honovich, Or  and Aharoni, Roee  and Herzig, Jonathan  and Taitelbaum, Hagai  and Kukliansy, Doron  and Cohen, Vered  and Scialom, Thomas  and Szpektor, Idan  and Hassidim, Avinatan  and Matias, Yossi",
    booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    pages = "3905--3920",
    doi = "10.18653/v1/2022.naacl-main.287",
}

@misc{reimers-2019-sentence-bert,
    title={Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks}, 
    author={Nils Reimers and Iryna Gurevych},
    year={2019},
    eprint={1908.10084},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    doi={10.48550/arXiv.1908.10084},
}

@misc{wang2023openchat,
    title={OpenChat: Advancing Open-source Language Models with Mixed-Quality Data}, 
    author={Guan Wang and Sijie Cheng and Xianyuan Zhan and Xiangang Li and Sen Song and Yang Liu},
    year={2023},
    eprint={2309.11235},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    doi={10.48550/arXiv.2309.11235},
}

@article{maynez2020faithfulness,
  title={On faithfulness and factuality in abstractive summarization},
  author={Maynez, Joshua and Narayan, Shashi and Bohnet, Bernd and McDonald, Ryan},
  journal={arXiv preprint arXiv:2005.00661},
  year={2020}
}

@article{shuster2021retrieval,
  title={Retrieval augmentation reduces hallucination in conversation},
  author={Shuster, Kurt and Poff, Spencer and Chen, Moya and Kiela, Douwe and Weston, Jason},
  journal={arXiv preprint arXiv:2104.07567},
  year={2021}
}

@misc{dziri2022faithdial,
      title={FaithDial: A Faithful Benchmark for Information-Seeking Dialogue}, 
      author={Nouha Dziri and Ehsan Kamalloo and Sivan Milton and Osmar Zaiane and Mo Yu and Edoardo M. Ponti and Siva Reddy},
      year={2022},
      eprint={2204.10757},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{HaluEval,
  author = {Junyi Li and Xiaoxue Cheng and Wayne Xin Zhao and Jian-Yun Nie and Ji-Rong Wen },
  title = {HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models},
  year = {2023},
  journal={arXiv preprint arXiv:2305.11747},
  url={https://arxiv.org/abs/2305.11747}
}

@article{huang2021factual,
  title={The factual inconsistency problem in abstractive text summarization: A survey},
  author={Huang, Yichong and Feng, Xiachong and Feng, Xiaocheng and Qin, Bing},
  journal={arXiv preprint arXiv:2104.14839},
  year={2021}
}

@inproceedings{burtsev2018deeppavlov,
  title={DeepPavlov: An Open Source Library for Conversational AI},
  author={Burtsev, Mikhail and Seliverstov, Alexander and Airapetyan, Rafael and Arkhipov, Mikhail and Baymurzina, Dilyara and Bushkov, Nickolay and Gureenkova, Olga and Khakhulin, Taras and Kuratov, Yuri and Kuznetsov, Denis and Konovalov, Vasily},
  journal={NIPS 2018},
  booktitle={NIPS},
  url={https://openreview.net/pdf?id=BJzyCF6Vn7},
  year={2018}
}

@InProceedings{chizhikova,
author="Chizhikova, Anastasia
and Konovalov, Vasily
and Burtsev, Mikhail",
editor="Kryzhanovsky, Boris
and Dunin-Barkowski, Witali
and Redko, Vladimir
and Tiumentsev, Yury",
title="Multilingual Case-Insensitive Named Entity Recognition",
booktitle="Advances in Neural Computation, Machine Learning, and Cognitive Research VI",
year="2023",
publisher="Springer International Publishing",
address="Cham",
pages="448--454",
isbn="978-3-031-19032-2",
doi="10.1007/978-3-031-19032-2_46"
}

@misc{bowman2015large,
      title={A large annotated corpus for learning natural language inference}, 
      author={Samuel R. Bowman and Gabor Angeli and Christopher Potts and Christopher D. Manning},
      year={2015},
      eprint={1508.05326},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@article{williams2017broad,
  title={A broad-coverage challenge corpus for sentence understanding through inference},
  author={Williams, Adina and Nangia, Nikita and Bowman, Samuel R},
  journal={arXiv preprint arXiv:1704.05426},
  year={2017}
}

@article{thorne2018fever,
  title={FEVER: a large-scale dataset for fact extraction and VERification},
  author={Thorne, James and Vlachos, Andreas and Christodoulopoulos, Christos and Mittal, Arpit},
  journal={arXiv preprint arXiv:1803.05355},
  year={2018}
}
@inproceedings{ostyakova-etal-2023-chatgpt,
    title = "{C}hat{GPT} vs. Crowdsourcing vs. Experts: Annotating Open-Domain Conversations with Speech Functions",
    author = "Ostyakova, Lidiia  and
      Smilga, Veronika  and
      Petukhova, Kseniia  and
      Molchanova, Maria  and
      Kornev, Daniel",
    editor = "Stoyanchev, Svetlana  and
      Joty, Shafiq  and
      Schlangen, David  and
      Dusek, Ondrej  and
      Kennington, Casey  and
      Alikhani, Malihe",
    booktitle = "Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue",
    month = sep,
    year = "2023",
    address = "Prague, Czechia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.sigdial-1.23",
    doi = "10.18653/v1/2023.sigdial-1.23",
    pages = "242--254",
    abstract = "This paper deals with the task of annotating open-domain conversations with speech functions. We propose a semi-automated method for annotating dialogs following the topic-oriented, multi-layered taxonomy of speech functions with the use of hierarchical guidelines using Large Language Models. These guidelines comprise simple questions about the topic and speaker change, sentence types, pragmatic aspects of the utterance, and examples that aid untrained annotators in understanding the taxonomy. We compare the results of dialog annotation performed by experts, crowdsourcing workers, and ChatGPT. To improve the performance of ChatGPT, several experiments utilising different prompt engineering techniques were conducted. We demonstrate that in some cases large language models can achieve human-like performance following a multi-step tree-like annotation pipeline on complex discourse annotation, which is usually challenging and costly in terms of time and money when performed by humans.",
}
@article{schuster2021get,
  title={Get your vitamin C! robust fact verification with contrastive evidence},
  author={Schuster, Tal and Fisch, Adam and Barzilay, Regina},
  journal={arXiv preprint arXiv:2103.08541},
  year={2021}
}

@article{zhang2019paws,
  title={PAWS: Paraphrase adversaries from word scrambling},
  author={Zhang, Yuan and Baldridge, Jason and He, Luheng},
  journal={arXiv preprint arXiv:1904.01130},
  year={2019}
}

@inproceedings{khot2018scitail,
  title={Scitail: A textual entailment dataset from science question answering},
  author={Khot, Tushar and Sabharwal, Ashish and Clark, Peter},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={32},
  number={1},
  year={2018}
}

@inproceedings{squad,
  title={Exploring the Bert Cross-Lingual Transfer for Reading Comprehension},
  author={Konovalov, Vasily and Gulyaev, Pavel and Sorokin, Alexey and Kuratov, Yury and Burtsev, Mikhail},
  booktitle={Computational Linguistics and Intellectual Technologies},
  pages={445--453},
  url={http://www.dialog-21.ru/media/5100/konovalovvpplusetal-118.pdf},
  doi={10.28995/2075-7182-2020-19-445-453},
  isbn={978-5-7281-2947-9},
  year={2020}
  }

@inproceedings{konovalov_collecting_2016,
	address = {Los Angeles},
	title = {Collecting {Better} {Training} {Data} using {Biased} {Agent} {Policies} in {Negotiation} {Dialogues}},
	url = {http://workshop.colips.org/wochat/documents/RP-270.pdf},
	abstract = {When naturally occurring data is characterized by a highly skewed class distribution, supervised learning often benefits from reducing this skew. Human-agent dialogue data is commonly highly skewed when using standard agent policies. Hence, we suggest that agent policies need to be reconsidered in the context of training data collection. Specifically, in this work we implemented biased agent policies that are optimized for data collection in the negotiation domain. Empirical evaluations show that our method is successful in collecting a reasonably balanced corpus in the highly skewed Job-Candidate domain. Furthermore, using this balanced corpus to train a negotiation intent classifier yields notable performance improvements relative to naturally distributed data.},
	booktitle = {Proceedings of {WOCHAT}, the {Second} {Workshop} on {Chatbots} and {Conversational} {Agent} {Technologies}},
	publisher = {Zerotype},
	author = {Konovalov, Vasily and Melamud, Oren and Artstein, Ron and Dagan, Ido},
	month = sep,
	year = {2016},
	keywords = {Virtual Humans}
}

@misc{prokhorenkova2019catboost,
    title={CatBoost: unbiased boosting with categorical features}, 
    author={Liudmila Prokhorenkova and Gleb Gusev and Aleksandr Vorobev and Anna Veronika Dorogush and Andrey Gulin},
    year={2019},
    eprint={1706.09516},
    archivePrefix={arXiv},
    primaryClass={cs.LG},
    doi={10.48550/arXiv.1706.09516},
}

@article{random-forest,
    title={Random Forests},
    author={Breiman, L.},
    journal={Machine Learning},
    volume={45},
    pages={5--32},
    year={2001},
    doi={10.1023/A:1010933404324},
}

@inproceedings{NIPS2017_6449f44a,
    title = {LightGBM: A Highly Efficient Gradient Boosting Decision Tree},
    author = {Ke, Guolin and Meng, Qi and Finley, Thomas and Wang, Taifeng and Chen, Wei and Ma, Weidong and Ye, Qiwei and Liu, Tie-Yan},
    booktitle = {Advances in Neural Information Processing Systems},
    editor = {I. Guyon and U. Von Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
    pages = {},
    publisher = {Curran Associates, Inc.},
    volume = {30},
    year = {2017},
    url = {https://proceedings.neurips.cc/paper_files/paper/2017/file/6449f44a102fde848669bdd9eb6b76fa-Paper.pdf},
}

@article{scikit-learn,
    title   = {Scikit-learn: Machine Learning in Python},
    author  = {Fabian Pedregosa and Ga{{\"e}}l Varoquaux and Alexandre Gramfort and Vincent Michel and Bertrand Thirion and Olivier Grisel and Mathieu Blondel and Peter Prettenhofer and Ron Weiss and Vincent Dubourg and Jake Vanderplas and Alexandre Passos and David Cournapeau and Matthieu Brucher and Matthieu Perrot and {{\'E}}douard Duchesnay},
    journal = {Journal of Machine Learning Research},
    year    = {2011},
    volume  = {12},
    number  = {85},
    pages   = {2825-2830},
    url     = {http://jmlr.org/papers/v12/pedregosa11a.html},
}

@inproceedings{optuna_2019,
    title={Optuna: A Next-generation Hyperparameter Optimization Framework},
    author={Akiba, Takuya and Sano, Shotaro and Yanase, Toshihiko and Ohta, Takeru and Koyama, Masanori},
    booktitle={Proceedings of the 25th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    year={2019},
    doi={10.48550/arXiv.1907.10902},
}
