Continuous Homeostatic Reinforcement Learning for Self-Regulated Autonomous Agents. - Hugo Laurençon; Charbel-Raphaël Ségerie; Johann Lussange; Boris S. Gutkin (CoRR, 2021)

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. - Stephen Casper; Xander Davies; Claudia Shi; Thomas Krendl Gilbert; Jérémy Scheurer; Javier Rando; Rachel Freedman; Tomasz Korbak; David Lindner; Pedro Freire; Tony Tong Wang; Samuel Marks; et al. (Trans. Mach. Learn. Res., 2023)

Continuous Time Continuous Space Homeostatic Reinforcement Learning (CTCS-HRRL) : Towards Biological Self-Autonomous Agent. - Hugo Laurençon; Yesoda Bhargava; Riddhi Zantye; Charbel-Raphaël Ségerie; Johann Lussange; Veeky Baths; Boris Gutkin (CoRR, 2024)

BELLS: A Framework Towards Future Proof Benchmarks for the Evaluation of LLM Safeguards. - Diego Dorn; Alexandre Variengien; Charbel-Raphaël Ségerie; Vincent Corruble (CoRR, 2024)

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? - Ben Bucknall; Saad Siddiqui; Lara Thurnherr; Conor McGurk; Ben Harack; Anka Reuel; Patricia Paskov; Casey Mahoney; Sören Mindermann; Scott Singer; Vinay Hiremath; Charbel-Raphaël Ségerie; et al. (FAccT, 2025)

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? - Ben Bucknall; Saad Siddiqui; Lara Thurnherr; Conor McGurk; Ben Harack; Anka Reuel; Patricia Paskov; Casey Mahoney; Sören Mindermann; Scott Singer; Vinay Hiremath; Charbel-Raphaël Ségerie; et al. (CoRR, 2025)

Safety by Measurement: A Systematic Literature Review of AI Safety Evaluation Methods. - Markov Grey; Charbel-Raphaël Ségerie (CoRR, 2025)

The bitter lesson of misuse detection. - Hadrien Mariaccia; Charbel-Raphaël Ségerie; Diego Dorn (CoRR, 2025)

The AI Risk Spectrum: From Dangerous Capabilities to Existential Threats. - Markov Grey; Charbel-Raphaël Ségerie (CoRR, 2025)