NPTI induces positive and negative Big-Five poles by intervening directly in FFN activations at inference time, without training or changing model weights. PersonalityBench combines descriptions derived from IPIP-NEO-300 facets with generated situational questions over UltraChat topics. For each trait, Llama-3-8B-Instruct answers the same questions under opposing descriptions; the method measures, per coordinate, the difference in probability that the SiLU gate output is positive and selects differences above +10% or below -10%. During generation, NPTI increases target-pole coordinates with a function weighted by delta and the coordinate's 95th percentile, while clamping opposite-pole coordinates at a maximum of zero. On the SocialIQA-derived automatic test, NPTI reports an aggregate mean of 9.43 and variance of 0.49: it equals P2's mean with lower variance and trails LoRA SFT by 0.18 points. Five judges rank five methods on 200 questions; NPTI has the best overall average rank (2.27) and leads Extraversion and Neuroticism, while Simple Prompt, P2, and SFT respectively lead Agreeableness, Conscientiousness, and Openness. It beats both prompts on all five Qwen traits but only about half of the Mistral and Gemma comparisons. The intervention is not neutral to general capability: almost every condition lowers at least one metric, Neuroticism-positive loses up to 7 points on CommonsenseQA, and only Conscientiousness-positive improves all four slightly. The defensible reading is that NPTI is a competitive white-box mechanism for steering text toward recognizable trait behavior, not a persistent psychological personality change. The artifacts reinforce that caution. The ten public sets contain 10,278-31,790 coordinates per pole; their union covers 27.15% of Llama's FFN gates, and 47.48% of that union occurs in at least two traits. These are broad, overlapping distributed correlates, not exclusive personality neurons. The public repository also does not reproduce the paper as written: it applies an undisclosed random 90% activation mask without a seed, executes only the reversed pole, judges reversed outputs with positive-trait factors, and routes P2 through the wrong template. It omits PAS, ActAdd, SFT, raw results, and alternative-model artifacts, publishes a plaintext API credential, and pins conflicting dependencies. The paper therefore contributes an important technical idea and relevant comparative evidence, but claims of stability, neuron specificity, general parity with fine-tuning, and reproducibility must remain limited to the evaluated behavior and do not justify deployment.
Research question
Can the textual expression of the positive and negative poles of the Big Five be localized and controlled by identifying FFN coordinates whose activation probability differs under opposite descriptions, and can that intervention compete with prompting, activation addition and LoRA SFT without modifying the weights?