Preprint Open access
Generalization Is Stability, Not Accuracy: Multi-Axis Evaluation of LLMs
Generalization in large language models (LLMs) is the ability to produce consistent and semantically stable outputs when the same input is expressed in different ways. Existing work typically evaluates generalization through aggregate accuracy on a single prompt format, task, or set of variations, which conflates robus …