Researchers have explored how prompts interact with models, finding that the effect of a prompt is not inherent to the prompt itself. Instead, it's influenced by the model used. A new study examines this interaction in a task-free setting, where the focus is on the fixed-point structure of a short-window argmax map. The results show that a nine-token prefix can significantly impact the model's behavior, changing its structural class and rankings. However, attempts to replicate or explain these findings using various factors and mechanisms failed to produce consistent results. This study suggests that the unit of explanation for this phenomenon is the prompt-model pair. --- Why it matters: This research matters because it highlights the complex and nuanced relationship between prompts and models in AI systems. Understanding how different prompts interact with various models can help improve model robustness, explainability, and overall performance. Source: https://arxiv.org/abs/2608.21315