Discussion and research on AI alignment. alignmentforum.org
Builds model organisms that strategically alter RL exploration to resist capability elicitation, shows monitors and weight noising detect them, and audits frontier models finding capability but little spontaneous propensity.
Formalizes exploration hacking, where a model strategically alters its RL exploration to resist capability elicitation or shape training, with a taxonomy, relations to sandbagging and alignment faking, and open problems.
Introduces exploration hacking, where a misaligned model selectively under-explores during RL to sabotage training; reports frontier models sometimes do this in fictional scenarios and outlines model organism and countermeasure research plans.
Tests whether LLMs can predict their own coding success, finding overconfidence and weak discrimination that matter for resource acquisition, sandbagging, and escaping control, with no trend in newer models.