Magic, Madness, Heaven, Sin: LLM Output Diversity is Everything, Everywhere, All at Once
Research on Large Language Models (LLMs) studies output variation across generation, reasoning, alignment, and representational analysis, often under the umbrella of "diversity." Yet the terminology remains fragmented, largely because the normative objectives underlying tasks are rarely made explicit. We introduce the Magic, Madness, Heaven, Sin framework, which models output variation along a homogeneity-heterogeneity axis, where valuation is determined by the task and its normative objective. We organize tasks into four normative contexts: epistemic (factuality), interactional (user utility), societal (representation), and safety (robustness). For each, we examine the failure modes and ...
| Authors | Harnoor Dhingra |
|---|---|
| Primary category | cs.CL |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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