Deep Noir: Autonomous Steering Discovery via Architectural Chronometry in Transformer Models
Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a framework that uses Logit Lens convergence and causal head-level attribution to autonomously discover optimal steering parameters. Across three scales (1B x 3, 2-3B x 2, and 7-9B x 4), our engine achieves 16.7 percentage-point improvement on spam…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
