Improving and Assessing the Fidelity of Large Language Models Alignment to Online Communities. Chu, M. D., He, Z., Dorn, R., & Lerman, K. In Chiruzzo, L., Ritter, A., & Wang, L., editors, Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2025 - Volume 1: Long Papers, Albuquerque, New Mexico, USA, April 29 - May 4, 2025, pages 88–111, 2025. Association for Computational Linguistics.
Improving and Assessing the Fidelity of Large Language Models Alignment to Online Communities [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/naacl/ChuHDL25,
  author       = {Minh Duc Chu and
                  Zihao He and
                  Rebecca Dorn and
                  Kristina Lerman},
  editor       = {Luis Chiruzzo and
                  Alan Ritter and
                  Lu Wang},
  title        = {Improving and Assessing the Fidelity of Large Language Models Alignment
                  to Online Communities},
  booktitle    = {Proceedings of the 2025 Conference of the Nations of the Americas
                  Chapter of the Association for Computational Linguistics: Human Language
                  Technologies, {NAACL} 2025 - Volume 1: Long Papers, Albuquerque, New
                  Mexico, USA, April 29 - May 4, 2025},
  pages        = {88--111},
  publisher    = {Association for Computational Linguistics},
  year         = {2025},
  url          = {https://doi.org/10.18653/v1/2025.naacl-long.5},
  doi          = {10.18653/V1/2025.NAACL-LONG.5},
  timestamp    = {Fri, 13 Jun 2025 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/naacl/ChuHDL25.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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