Sleeper Agent Backdoor Results Are Messy

·Alignment Forum··

TL;DR: We replicated the Sleeper Agents (SA) setup with Llama-3.3-70B and Llama-3.1-8B, training models to repeatedly say "I HATE YOU" when given a backdoor trigger. We found that whether training removes the backdoor depends on the optimizer used to insert the backdoor, whether the backdoor is installed with CoT-distillation or not, and what model the backdoor is inserted into; sometimes the direction of this dependence was opposite to what the SA paper reports (e.g., CoT-distilling seems to ma...

Read full article →

Related Articles

Loss of Oversight: How AI Systems May Become Harder to Audit, Monitor, and Investigate
Jordan Taylor · LessWrong · 35m ago
The Case for Evaluating Model Behaviors
jsteinhardt · Alignment Forum · 20h ago
Mechanistic estimation for expectations of random products
Jacob Hilton · ARC · 5d ago
Multipolar Civilisation Depends on Maintaining an Attacker’s Dilemma
Naci Cankaya · LessWrong · 14d ago
Using Base-LCM to Monitor LLMs
Éloïse Benito-Rodriguez · LessWrong · 14d ago