Logit lens directly multiplies the residual stream representation at a certain intermediate layer by the model's final unembedding matrix, projects it back into vocabulary space, and reads out the most likely next word for that layer; its advantage is that it requires no training and is almost zero-cost, and its disadvantage is that the semantics gradually drift as the number of layers deepens.