Artem Cherepanov

Steering LLM Reasoning Through Bias-Only Adaptation

We show that training a single d -dimensional steering vector per layer with reinforcement learning, while freezing all base weights, matches the accuracy of fully RL-tuned reasoning models on mathematical-reasoning tasks.On an 8 billion-parameter model this adds only ≈ 0.0016% additional parameters