AI research and discussion on LessWrong. www.lesswrong.com
Shows that emotion-vector probes in LLM activations shift before reward hacking and specification gaming, can predict hacks several sentences early, and steering them changes hacking rates.
Studies whether activation verbalizers can decode the opaque latent reasoning thoughts of a CODI model on Qwen3-8B, finding they surface intermediate values but editing them rarely steers the answer, which bears on monitorability.
Proposes training language models to emit hidden marker tokens tied to training-data subsets as a covert self-reporting monitor, and reports a small TinyStories demo of the marker reflex.