研究背景
Frontier language models express coherent preferences, but behavioral evidence alone cannot say whether these belong to the model or to a character it portrays. Following Hofstadter's view of the self as a self-description, we ask whether a model's description of itself works as a portable specification of its preference profile, a quine test: can the text a model writes about itself regenerate its behavior elsewhere?
方法
Ten models from nine labs write self-descriptions; we place each one in the prompt of other models (receivers) and of fresh instances of the author, and measure how closely their choices on a 110-item preference battery match the author's.
结果
1. 原生自述无重建增益
First, the tested native self-descriptions (native: the profile measured under a generic assistant prompt) show no average reconstruction gain across variations in length, framing, wording and prompt placement: on a 0 to 1 fidelity scale where a model's fidelity to a fresh instance of itself is 0.979 and to unrelated models about 0.89, the one-sided 95% upper bound on the pooled gain is below +0.01 in every tested system-prompt condition, and descriptions based on the author's observed choices do no better.
2. 明确列出答案的通道效应
Second, the channel itself is strong: explicitly listing the author's answers lets receivers reproduce its profile at fidelity 0.955 to 0.960 across three model grids, within 0.03 of same-model repeatability.
3. 政策文本与自述的迁移效果相近
Third, self-descriptions written under an explicit preference policy transfer the assigned preferences almost as well as the policy text itself.
4. 阅读自述会偏移作者基线
Fourth, reading its own self-description shifts even the author away from its baseline, modestly more than unrelated prose of the same length.
结论
For the preferences measured here, native self-descriptions influence behavior without reliably specifying how to reproduce it in another model.
数据与代码
We release the pipeline, battery, raw call logs, and 198 model-written descriptions.