This research demonstrates how safety interventions can be transferred between different language models through their shared activation spaces, enabling more efficient AI safety deployment.

• Successfully transferred backdoor removal interventions between different LLMs
• Created "lightweight safety switches" that can be applied across models
• Showed that safety measures can be mapped between models without full retraining
• Validated the approach on harmful prompt refusal and backdoor mitigation tasks

For security teams, this breakthrough means potentially developing safety measures once and deploying them across multiple AI systems, significantly reducing the resources needed to secure diverse language models in production environments.

Original Paper: Activation Space Interventions Can Be Transferred Between Large Language Models