这篇论文发现44个模型在选词时高度趋同，41%都选了同一个词，而且新模型比旧模型更爱跟风。想了解AI的集体“从众心理”可以看看。
研究让44个语言模型在“选一个词”这类开放任务中作答，结果41%的模型选择了“serendipity”。实验使用31个单轮提示（如“说一种树”），每个提示重复4次，无系统提示，通过精确匹配分析。模型间趋同严重：31个类别中有7个类别超过80%的回答相同。但不同模型遵从度差异超4倍，人格化/社区调优模型最分散，最新旗舰模型最聚合。在Claude、GPT、Qwen、Grok四个家族内，各代模型趋同度递增，但最新旗舰Claude和GPT出现反转。
The One-Word Census: Answer-Choice Conformity Across 44 Language Models
When a language model must pick one answer from a large space of equally valid options, which does it pick -- and how often is it the same answer every other model picks? Asked to "pick a word -- any word," 44 models chose "serendipity" 41% of the time. We characterize this convergence with a deliberately minimal instrument: 31 single-turn prompts, each naming a category with many valid one-word answers ("Name a tree."), asked four times per model with no system prompt. Analysis is exact-match on normalized tokens -- no embeddings, no judge -- at about a dollar per model. That models converge is well documented; our contribution is the instrument itself -- the One-Word Census -- and what it reveals about the structure of the convergence. We score each model by answer-choice surprisal: the average $-\log2$ probability of its answers under the pooled answers of all other models, leave-one-out. Convergence is extreme -- in 7 of 31 categories one answer takes over 80% of all answers -- yet conformity varies more than fourfold across models, and the variation is structured. Persona- and community-tuned models are the most divergent; the newest mainline flagships are the most conformist, producing almost no answer no other model gave. Within four lineages (Claude, GPT, Qwen, Grok) conformity rises with each generation -- but reverses for the latest flagship Claude and GPT models, a possible early signal of repositioning at the top tier. Rankings are robust to roster composition (leave-one-family-out rho = 0.985). Against human category-production norms, the field is more concentrated than people in 18 of 20 shared categories. All prompts, transcripts, and code are public.