3 papers
cs.AI2026
Probing the Misaligned Thinking Process of Language Models
Kaiwen Zhou, Constantin Venhoff, Jonathan Michala +2
Large language models exhibit a growing range of misaligned behaviors such as strategic deception, sandbagging, and self-preservation. As they are increasingly deployed in high-sta…
cs.CL2026
Gemma Needs Help: Investigating and Mitigating Emotional Instability in LLMs
Anna Soligo, Vladimir Mikulik, William Saunders
Large language models can generate responses that resemble emotional distress, and this raises concerns around model reliability and safety. We introduce a set of evaluations to in…
cs.LG2025
RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts
Hjalmar Wijk, Tao Lin, Joel Becker +20
Frontier AI safety policies highlight automation of AI research and development (R&D) by AI agents as an important capability to anticipate. However, there exist few evaluations fo…