Personality Latents: Conditioning Frozen Language Models on Individuals from Their Own Writing
Controlling the personality of a language model usually relies on written profiles or named trait categories, so it can only express what an author writes down or what a taxonomy names. We instead propose Personality Latents (PL), which learn a latent for each person from their own writing, with no personality labels and no authored profile, and inject it into a frozen language model as a soft prefix. Following generative latent optimization, each training person receives a free latent that is optimized through the frozen model itself, while an encoder learns to predict these latents so that a new person needs only one forward pass, with optional refinement at test time. We evaluate on he...
| Authors | Gunhee Cho, Yun-Gyung Cheong |
|---|---|
| Primary category | cs.CL |
| Published | 27 October 2026 |
| Last updated at source | 27 October 2026 |
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