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

@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}
}
@inproceedings{naseem-etal-2026-polar,

  title     = {{S}em{E}val-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization},

  author    = {Naseem, Usman and

               Geislinger, Robert and

               Ren, Juan and

               Kohail, Sarah and

               Garrido Veliz, Rudy and

               Sam Sahil, P and

               Zhang, Yiran and

               Stranisci, Marco Antonio and

               Abdulmumin, Idris and

               Alacam, {"O}zge and

               Acar{"u}rk, Cengiz and

               Jabr, Aisha and

               Anwar, Saba and

               Ayele, Abinew Ali and

               Tutubalina, Elena and

               Htet, Aung Kyaw and

               Wang, Xintong and

               Thapa, Surendrabikram and

               Chakraborty, Tanmoy and

               Kodati, Dheeraj and

               Moradizeyveh, Sahar and

               Alam, Firoj and

               Thu, Ye Kyaw and

               Parida, Shantipriya and

               Qazi, Ihsan Ayyub and

               Onyango, Nelson Odhiambo and

               Siro, Clemencia and

               Ahmad, Ibrahim Said and

               Wanzare, Lilian and

               Ali, Adem Chanie and

               Semmann, Martin and

               Biemann, Chris and

               Muhammad, Shamsuddeen Hassan and

               Yimam, Seid Muhie},

  booktitle = {Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026)},

  year      = {2026},

  publisher = {Association for Computational Linguistics},

}
@article{IANDOLI2021120924,
title = {The impact of group polarization on the quality of online debate in social media: A systematic literature review},
journal = {Technological Forecasting and Social Change},
volume = {170},
pages = {120924},
year = {2021},
issn = {0040-1625},
doi = {https://doi.org/10.1016/j.techfore.2021.120924},
url = {https://www.sciencedirect.com/science/article/pii/S0040162521003565},
author = {Luca Iandoli and Simonetta Primario and Giuseppe Zollo},
keywords = {Group polarization, Echo-chambers, Social media, Social networks, Online discussions, Online argumentation},
abstract = {Social media are often accused of worsening the quality of online debate. In this paper, we focus on group polarization in the context of social media-enabled interaction, a dysfunctional group dynamic by which participants become more extreme in their initial position on an issue. Through a systematic literature review, we identified a corpus of 121 research papers investigating polarization in social media and other online conversational platforms and reviewed the main empirical findings, as well as theoretical and methodological approaches. We use this knowledge base to assess some recurrent accusations against social media in terms of their supposed tendency to worsen online debate. Our analysis shows that, while some concerns have been exaggerated, social media do contribute to increase polarization either by amplifying and escalating social processes that also occur offline or in specific ways enabled by their design affordances, which also make these platforms prone to manipulation. We argue against suggestions aimed at reducing freedom of speech in cyberspace and identify in inadequate regulation and lack of ethical design as the leading causes of social media-enabled group dysfunctions, highlighting research areas that can support the creation of higher quality online discursive spaces.}
}

@article{
zafar2025investigating,
  title={INVESTIGATING POLITICAL IDEOLOGY IN ENGLISH AND URDU NEWSPAPER EDITORIALS A CORPUS-BASED COMPARATIVE STUDY},
  author={Zafar, Shanza and Asghar, Prof. Dr. Ijaz and Nawaz, Dr. Naveed and Bilal, Prof. Dr. Hafiz Ahmad},
  journal={Journal of Applied Linguistics and TESOL (JALT)},
  volume={8},
  number={4},
  year={2025},
  doi={10.63878/jalt1488},
  url={https://jalt.com.pk/index.php/jalt/article/view/1488}
}


@misc{verma2025milumultitaskindiclanguage,
      title={MILU: A Multi-task Indic Language Understanding Benchmark}, 
      author={Sshubam Verma and Mohammed Safi Ur Rahman Khan and Vishwajeet Kumar and Rudra Murthy and Jaydeep Sen},
      year={2025},
      eprint={2411.02538},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2411.02538}, 
}

@inproceedings{Saji_2025,
   title={RomanLens: The Role Of Latent Romanization In Multilinguality In LLMs},
   url={http://dx.doi.org/10.18653/v1/2025.findings-acl.1354},
   DOI={10.18653/v1/2025.findings-acl.1354},
   booktitle={Findings of the Association for Computational Linguistics: ACL 2025},
   publisher={Association for Computational Linguistics},
   author={Saji, Alan and Husain, Jaavid Aktar and Jayakumar, Thanmay and Dabre, Raj and Kunchukuttan, Anoop and Puduppully, Ratish},
   year={2025},
   pages={26410–26429} }

@misc{naseem2026polarbenchmarkmultilingualmulticultural,
      title={POLAR: A Benchmark for Multilingual, Multicultural, and Multi-Event Online Polarization}, 
      author={Usman Naseem and Robert Geislinger and Juan Ren and Sarah Kohail and Rudy Garrido Veliz and P Sam Sahil and Yiran Zhang and Marco Antonio Stranisci and Idris Abdulmumin and Özge Alacam and Cengiz Acartürk and Aisha Jabr and Saba Anwar and Abinew Ali Ayele and Simona Frenda and Alessandra Teresa Cignarella and Elena Tutubalina and Oleg Rogov and Aung Kyaw Htet and Xintong Wang and Surendrabikram Thapa and Kritesh Rauniyar and Tanmoy Chakraborty and Arfeen Zeeshan and Dheeraj Kodati and Satya Keerthi and Sahar Moradizeyveh and Firoj Alam and Arid Hasan and Syed Ishtiaque Ahmed and Ye Kyaw Thu and Shantipriya Parida and Ihsan Ayyub Qazi and Lilian Wanzare and Nelson Odhiambo Onyango and Clemencia Siro and Jane Wanjiru Kimani and Ibrahim Said Ahmad and Adem Chanie Ali and Martin Semmann and Chris Biemann and Shamsuddeen Hassan Muhammad and Seid Muhie Yimam},
      year={2026},
      eprint={2505.20624},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.20624}, 
}

@misc{feng2022languageagnosticbertsentenceembedding,
      title={Language-agnostic BERT Sentence Embedding}, 
      author={Fangxiaoyu Feng and Yinfei Yang and Daniel Cer and Naveen Arivazhagan and Wei Wang},
      year={2022},
      eprint={2007.01852},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2007.01852}, 
}

@misc{bahdanau2016neuralmachinetranslationjointly,
      title={Neural Machine Translation by Jointly Learning to Align and Translate}, 
      author={Dzmitry Bahdanau and Kyunghyun Cho and Yoshua Bengio},
      year={2016},
      eprint={1409.0473},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/1409.0473}, 
}

@misc{chung2020rethinkingembeddingcouplingpretrained,
      title={Rethinking embedding coupling in pre-trained language models}, 
      author={Hyung Won Chung and Thibault Févry and Henry Tsai and Melvin Johnson and Sebastian Ruder},
      year={2020},
      eprint={2010.12821},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2010.12821}, 
}


@inproceedings{brown2020languagemodelsfewshotlearners,
    title = {Language Models are Few-Shot Learners},
    author = {Brown, Tom and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared S and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and others},
    booktitle = {Advances in Neural Information Processing Systems},
    volume = {33},
    pages = {1877--1901},
    year = {2020}
}

@inproceedings{brown2020languagemodelsfewshotlearners,
 author = {Brown, Tom and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared D and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and Herbert-Voss, Ariel and Krueger, Gretchen and Henighan, Tom and Child, Rewon and Ramesh, Aditya and Ziegler, Daniel and Wu, Jeffrey and Winter, Clemens and Hesse, Chris and Chen, Mark and Sigler, Eric and Litwin, Mateusz and Gray, Scott and Chess, Benjamin and Clark, Jack and Berner, Christopher and McCandlish, Sam and Radford, Alec and Sutskever, Ilya and Amodei, Dario},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {1877--1901},
 publisher = {Curran Associates, Inc.},
 title = {Language Models are Few-Shot Learners},
 url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf},
 volume = {33},
 year = {2020}
}
@misc{wang2024chatgptgoodsentimentanalyzer,
      title={Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study}, 
      author={Zengzhi Wang and Qiming Xie and Yi Feng and Zixiang Ding and Zinong Yang and Rui Xia},
      year={2024},
      eprint={2304.04339},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2304.04339}, 
}

@inproceedings{10.1145/290941.291025,
author = {Carbonell, Jaime and Goldstein, Jade},
title = {The use of MMR, diversity-based reranking for reordering documents and producing summaries},
year = {1998},
isbn = {1581130155},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/290941.291025},
doi = {10.1145/290941.291025},
booktitle = {Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {335–336},
numpages = {2},
location = {Melbourne, Australia},
series = {SIGIR '98}
}

@misc{qwen2025qwen25technicalreport,
      title={Qwen2.5 Technical Report}, 
      author={Qwen and : and An Yang and Baosong Yang and Beichen Zhang and Binyuan Hui and Bo Zheng and Bowen Yu and Chengyuan Li and Dayiheng Liu and Fei Huang and Haoran Wei and Huan Lin and Jian Yang and Jianhong Tu and Jianwei Zhang and Jianxin Yang and Jiaxi Yang and Jingren Zhou and Junyang Lin and Kai Dang and Keming Lu and Keqin Bao and Kexin Yang and Le Yu and Mei Li and Mingfeng Xue and Pei Zhang and Qin Zhu and Rui Men and Runji Lin and Tianhao Li and Tianyi Tang and Tingyu Xia and Xingzhang Ren and Xuancheng Ren and Yang Fan and Yang Su and Yichang Zhang and Yu Wan and Yuqiong Liu and Zeyu Cui and Zhenru Zhang and Zihan Qiu},
      year={2025},
      eprint={2412.15115},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2412.15115}, 
}

@inproceedings{Nguyen_2025,
   title={Prompting with Phonemes: Enhancing LLMs’ Multilinguality for Non-Latin Script Languages},
   url={http://dx.doi.org/10.18653/v1/2025.naacl-long.599},
   DOI={10.18653/v1/2025.naacl-long.599},
   booktitle={Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)},
   publisher={Association for Computational Linguistics},
   author={Nguyen, Hoang H and Mahajan, Khyati and Yadav, Vikas and Salazar, Julian and Yu, Philip S. and Hashemi, Masoud and Maheshwary, Rishabh},
   year={2025},
   pages={11975–11994} }


@inproceedings{mortensen-etal-2018-epitran,
    title = "{E}pitran: Precision {G}2{P} for Many Languages",
    author = "Mortensen, David R.  and
      Dalmia, Siddharth  and
      Littell, Patrick",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Cieri, Christopher  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Hasida, Koiti  and
      Isahara, Hitoshi  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, H{\'e}l{\`e}ne  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios  and
      Tokunaga, Takenobu",
    booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)",
    month = may,
    year = "2018",
    address = "Miyazaki, Japan",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://aclanthology.org/L18-1429/"
}

@misc{chowdhury2026measuringsocialmediapolarization,
      title={Measuring Social Media Polarization Using Large Language Models and Heuristic Rules}, 
      author={Jawad Chowdhury and Rezaur Rashid and Gabriel Terejanu},
      year={2026},
      eprint={2601.00927},
      archivePrefix={arXiv},
      primaryClass={cs.SI},
      url={https://arxiv.org/abs/2601.00927}, 
}

@misc{boizard2025eurobertscalingmultilingualencoders,
      title={EuroBERT: Scaling Multilingual Encoders for European Languages}, 
      author={Nicolas Boizard and Hippolyte Gisserot-Boukhlef and Duarte M. Alves and André Martins and Ayoub Hammal and Caio Corro and Céline Hudelot and Emmanuel Malherbe and Etienne Malaboeuf and Fanny Jourdan and Gabriel Hautreux and João Alves and Kevin El-Haddad and Manuel Faysse and Maxime Peyrard and Nuno M. Guerreiro and Patrick Fernandes and Ricardo Rei and Pierre Colombo},
      year={2025},
      eprint={2503.05500},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2503.05500}, 
}
@article{loshchilov2016sgdr,
  title={SGDR: Stochastic Gradient Descent with Warm Restarts},
  author={Loshchilov, Ilya and Hutter, Frank},
  journal={arXiv preprint arXiv:1608.03983},
  year={2016}
}

@software{transformers,
  title = { Transformers - State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX},
  author = {HuggingFace and Wolf, T. and Debut, L. and Sanh, V. and Chaumond, J. and Delangue, C. and Moi, A. and Cistac, P. and Ma, C. and Jernite, Y. and Plu, J. and Xu, C. and Le Scao, T. and Gugger, S. and Drame, M. and Lhoest, Q. and Rush, A. M.},
  year = {2020},
  url = {https://github.com/huggingface/transformers},
  copyright = {Apache-2.0}
}

@inproceedings{conneau-etal-2020-unsupervised,
    title = "Unsupervised Cross-lingual Representation Learning at Scale",
    author = "Conneau, Alexis  and
      Khandelwal, Kartikay  and
      Goyal, Naman  and
      Chaudhary, Vishrav  and
      Wenzek, Guillaume  and
      Guzm{\'a}n, Francisco  and
      Grave, Edouard  and
      Ott, Myle  and
      Zettlemoyer, Luke  and
      Stoyanov, Veselin",
    editor = "Jurafsky, Dan  and
      Chai, Joyce  and
      Schluter, Natalie  and
      Tetreault, Joel",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.acl-main.747/",
    doi = "10.18653/v1/2020.acl-main.747",
    pages = "8440--8451",
    abstract = "This paper shows that pretraining multilingual language models at scale leads to significant performance gains for a wide range of cross-lingual transfer tasks. We train a Transformer-based masked language model on one hundred languages, using more than two terabytes of filtered CommonCrawl data. Our model, dubbed XLM-R, significantly outperforms multilingual BERT (mBERT) on a variety of cross-lingual benchmarks, including +14.6{\%} average accuracy on XNLI, +13{\%} average F1 score on MLQA, and +2.4{\%} F1 score on NER. XLM-R performs particularly well on low-resource languages, improving 15.7{\%} in XNLI accuracy for Swahili and 11.4{\%} for Urdu over previous XLM models. We also present a detailed empirical analysis of the key factors that are required to achieve these gains, including the trade-offs between (1) positive transfer and capacity dilution and (2) the performance of high and low resource languages at scale. Finally, we show, for the first time, the possibility of multilingual modeling without sacrificing per-language performance; XLM-R is very competitive with strong monolingual models on the GLUE and XNLI benchmarks. We will make our code and models publicly available."
}

@misc{kannen2025aestheticsculturalcompetencetexttoimage,
      title={Beyond Aesthetics: Cultural Competence in Text-to-Image Models}, 
      author={Nithish Kannen and Arif Ahmad and Marco Andreetto and Vinodkumar Prabhakaran and Utsav Prabhu and Adji Bousso Dieng and Pushpak Bhattacharyya and Shachi Dave},
      year={2025},
      eprint={2407.06863},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.06863}, 
}