% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").
@misc{vice2023aiwikipedia,
  author = {Vice},
  title = {{AI Is Tearing Wikipedia Apart}},
  year = {2023},
  howpublished = {\url{https://www.vice.com/en/article/v7bdba/ai-is-tearing-wikipedia-apart}},
  note = {Accessed: 2024-02-12}
}
@article{DBLP:journals/corr/abs-1906-04043,
  author       = {Sebastian Gehrmann and
                  Hendrik Strobelt and
                  Alexander M. Rush},
  title        = {{GLTR:} Statistical Detection and Visualization of Generated Text},
  journal      = {CoRR},
  volume       = {abs/1906.04043},
  year         = {2019},
  url          = {http://arxiv.org/abs/1906.04043},
  eprinttype    = {arXiv},
  eprint       = {1906.04043},
  timestamp    = {Fri, 14 Jun 2019 09:38:24 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1906-04043.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@misc{AITextDetector, 
    title     = {ZeroGPT : Reliable Chat GPT, GPT4 \& AI Content Detector},
    journal   = {AI Text Detector},
    author = {ZeroGPT},
    howpublished = {\url{https://www.zerogpt.com}}, 
    date      = {2023}
}
@misc{tian2023gptzero,
    publisher = {GPTZero},
    url       = {https://gptzero.me},
    year      = {2023},
    author    = {Tian, Edward and Cui, Alexander},
    title     = {GPTZero: Towards detection of AI-generated text using zero-shot and supervised methods}
}
@misc{gptkit,
  title = {{GPTKit: A Toolkit for Detecting AI Generated Text}},
  howpublished = {\url{https://gptkit.ai/}},
  author = {GptKit},
  note = {Accessed: 2024-02-12}
}
@article{wang2023m4,
      title={{M4}: Multi-generator, Multi-domain, and Multi-lingual
                   Black-Box Machine-Generated Text Detection}, 
      author={Yuxia Wang and
              Jonibek Mansurov and
              Petar Ivanov and
              Jinyan Su and
              Artem Shelmanov and
              Akim Tsvigun and
              Chenxi Whitehouse and
              Osama Mohammed Afzal and
              Tarek Mahmoud and
              Alham Fikri Aji and
              Preslav Nakov},
      year={2023},
      journal={arXiv:2305.14902},
      primaryClass={cs.CL}
}
@misc{touvron2023llama,
      title={LLaMA: Open and Efficient Foundation Language Models}, 
      author={Hugo Touvron and Thibaut Lavril and Gautier Izacard and Xavier Martinet and Marie-Anne Lachaux and Timothée Lacroix and Baptiste Rozière and Naman Goyal and Eric Hambro and Faisal Azhar and Aurelien Rodriguez and Armand Joulin and Edouard Grave and Guillaume Lample},
      year={2023},
      eprint={2302.13971},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@misc{koike2023outfox,
      title={OUTFOX: LLM-generated Essay Detection through In-context Learning with Adversarially Generated Examples}, 
      author={Ryuto Koike and Masahiro Kaneko and Naoaki Okazaki},
      year={2023},
      eprint={2307.11729},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@misc{he2023debertav3,
      title={DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing}, 
      author={Pengcheng He and Jianfeng Gao and Weizhu Chen},
      year={2023},
      eprint={2111.09543},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@misc{mccallum2012efficiently,
      title={Efficiently Inducing Features of Conditional Random Fields}, 
      author={Andrew McCallum},
      year={2012},
      eprint={1212.2504},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@inproceedings{joshi2020spanbert,
  title={SpanBERT: Improving Pre-training by Representing and Predicting Spans},
  author={Joshi, Mandar and Chen, Danqi and Liu, Yinhan and Weld, Daniel S and Zettlemoyer, Luke and Levy, Omer},
  booktitle={Transactions of the Association for Computational Linguistics},
  volume={8},
  pages={64--77},
  year={2020},
  publisher={MIT Press},
  url={https://arxiv.org/abs/1907.10529}
}
@misc{beltagy2020longformer,
      title={Longformer: The Long-Document Transformer}, 
      author={Iz Beltagy and Matthew E. Peters and Arman Cohan},
      year={2020},
      eprint={2004.05150},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@misc{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},
      year={2019},
      eprint={1907.11692},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@misc{kingma2017adam,
      title={Adam: A Method for Stochastic Optimization}, 
      author={Diederik P. Kingma and Jimmy Ba},
      year={2017},
      eprint={1412.6980},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@inproceedings{patkar-etal-2023-adityapatkar,
    title = "{R}o{BERT}a-Based Emotion Classification of Essays, Improving Performance on Imbalanced Data",
    author = "Patkar, Aditya  and
      Chandrashekhar, Suraj  and
      Kadiyala, Ram Mohan Rao",
    editor = "Barnes, Jeremy  and
      De Clercq, Orph{\'e}e  and
      Klinger, Roman",
    booktitle = "Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.wassa-1.46",
    doi = "10.18653/v1/2023.wassa-1.46",
    pages = "531--535",
    abstract = "This paper presents a study on using the RoBERTa language model for emotion classification of essays as part of the {`}Shared Task on Empathy Detection, Emotion Classification and Personality Detection in Interactions{'} organized as part of {`}WASSA 2023{'} at {`}ACL 2023{'}. Emotion classification is a challenging task in natural language processing, and imbalanced datasets further exacerbate this challenge. In this study, we explore the use of various data balancing techniques in combination with RoBERTa to improve the classification performance. We evaluate the performance of our approach (denoted by adityapatkar on Codalab) on a benchmark multi-label dataset of essays annotated with eight emotion categories, provided by the Shared Task organizers. Our results show that the proposed approach achieves the best macro F1 score in the competition{'}s training and evaluation phase. Our study provides insights into the potential of RoBERTa for handling imbalanced data in emotion classification. The results can have implications for the natural language processing tasks related to emotion classification.",
}
@inproceedings{NEURIPS2019_3e9f0fc9,
 author = {Zellers, Rowan and Holtzman, Ari and Rashkin, Hannah and Bisk, Yonatan and Farhadi, Ali and Roesner, Franziska and Choi, Yejin},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Defending Against Neural Fake News},
 url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/3e9f0fc9b2f89e043bc6233994dfcf76-Paper.pdf},
 volume = {32},
 year = {2019}
}
@InProceedings{wang-EtAl:2024:SemEval20245,
author = {Wang, Yuxia and Mansurov, Jonibek and Ivanov, Petar and su, jinyan and Shelmanov, Artem and Tsvigun, Akim and Mohammed Afzal, Osama and Mahmoud, Tarek and Puccetti, Giovanni and Arnold, Thomas and Whitehouse, Chenxi and Aji, Alham Fikri and Habash, Nizar and Gurevych, Iryna and Nakov, Preslav},
title = {SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection},
booktitle = {Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)},
month = {June},
year = {2024},
address = {Mexico City, Mexico},
publisher = {Association for Computational Linguistics},
pages = {2041--2063},
url = {https://aclanthology.org/2024.semeval2024-1.275}
}
@misc{wang2024m4gtbench,
      title={M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection}, 
      author={Yuxia Wang and Jonibek Mansurov and Petar Ivanov and Jinyan Su and Artem Shelmanov and Akim Tsvigun and Osama Mohanned Afzal and Tarek Mahmoud and Giovanni Puccetti and Thomas Arnold and Alham Fikri Aji and Nizar Habash and Iryna Gurevych and Preslav Nakov},
      year={2024},
      eprint={2402.11175},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@misc{openai2024gpt4,
      title={GPT-4 Technical Report}, 
      author={OpenAI},
      year={2024},
      eprint={2303.08774},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}