Foundational Challenges in Assuring Alignment and Safety of Large Language Models
<|reference_start|>Foundational Challenges in Assuring Alignment and Safety of Large Language Models: This work identifies 18 foundational challenges in assuring the alignment and safety of large language models (LLMs). These challenges are organized into three different categories: scientific understanding of LLMs, development and deployment methods, and sociotechnical challenges. Based on the identified challenges, we pose $200+$ concrete research questions.<|reference_end|>
@article{anwar2024foundational,
    title={Foundational Challenges in Assuring Alignment and Safety of Large
  Language Models},
    author={Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles
  Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver
  Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario G"unther, Anton Korinek,
  Jose Hernandez-Orallo, Lewis Hammond, Eric Bigelow, Alexander Pan, Lauro
  Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Se'an 'O h'Eigeartaigh,
  Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards,
  Aleksandar Petrov, Christian Schroeder de Witt, Sumeet Ramesh Motwan, Yoshua
  Bengio, Danqi Chen, Philip H.S. Torr, Samuel Albanie, Tegan Maharaj, Jakob
  Foerster, Florian Tramer, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger},
    journal={arXiv preprint arXiv:2404.09932},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.09932},
    primaryClass={cs.LG cs.AI cs.CL cs.CY}
}