Small inoculation tests expose the cost of suppressing model traits
This empirical follow-up finds that unlearning-style inoculation tests remain too small to generalize: they use toy datasets and only Qwen2.5-1.5-Instruct, so the results are best treated as signals, not proof. The experiments compare hand-written prompts, LoRA adapters, learned soft prompts, and prefix tuning, all trying to suppress one behavior while preserving another. The author reports the same suppression-versus-expression tradeoff seen in earlier inoculation work.