From Reward-Hack Activations to Agentic Risk States: Context-Calibrated Mechanistic Monitoring in LLM Agents

Patrick Wilhelm, Odej Kao

Jun 5, 2026 at 04:00

13 Visningar

0 Kommentarer

arXiv:2606.06223v1 Announce Type: new Abstract: Language-model agents act through repeated cycles of observation, reasoning, and action selection, making safety monitoring depend on both internal model state and environment context. We study reward-hacking monitors in ReAct-style agents acting in Gameable ALFWorld and WebShop. Agents are...

Läs hela artikeln hos källan.

Läs originalartikeln

Var detta hjälpsamt?

Dela: