3 papers
cs.LG2026
Evil Spectra: How Optimisers can Amplify or Suppress Emergent Misalignment
Jason R. Brown, Patrick Leask, Lev McKinney
Emergent misalignment (EM) is a recently discovered phenomenon in LLMs where fine-tuning on a narrow misaligned task, such as writing insecure code, leads to broadly misaligned beh…
cs.CL2025
KL-Regularised Q-Learning: A Token-level Action-Value perspective on Online RLHF
Jason R Brown, Lennie Wells, Edward James Young +1
Proximal Policy Optimisation (PPO) is an established and effective policy gradient algorithm used for Language Model Reinforcement Learning from Human Feedback (LM-RLHF). PPO perfo…
cs.AI2025
Manipulation Attacks by Misaligned AI: Risk Analysis and Safety Case Framework
Rishane Dassanayake, Mario Demetroudi, James Walpole +3
Frontier AI systems are rapidly advancing in their capabilities to persuade, deceive, and influence human behaviour, with current models already demonstrating human-level persuasio…