LLM Self-Recognition: Steering and Retrieving Activation Signatures 事件

LLM Self-Recognition: Steering and Retrieving Activation Signatures arXiv:2606.06315v1 Announce Type: new Abstract: Recent advances in interpretability suggest that large language models (LLMs) implicitly encode signals in their generated text that enable self-recognition of their outputs. We demonstrate that this capability is reliable, even in low-entropy scenarios, and that it can be amplified through targeted intervention. By steering the internal residual stream during generation with a ra