What do LLMs think when you don't tell them what to think about?

What this post added

This post introduces the concept of studying LLM behavior under near-unconstrained generation (minimal, topic-neutral prompts) to reveal inherent model priors. It details findings on distinct topical preferences across model families (GPT-OSS favoring programming/math, Llama leaning literary, DeepSeek religious, Qwen multiple-choice), depth differences in technical content generation, and model-specific degenerate output patterns (e.g., URLs, formatting artifacts). This expands the LLM Evaluation Framework by adding a new dimension of analysis beyond task-specific prompting.