Interpretable Humans, Alien LLMs: Expert Analysis of Latent Structures in Assessment Responses
The evaluation of large language models (LLMs) relies heavily on human-designed assessments, implicitly assuming that AI and humans employ similar underlying cognitive constructs. Challenging this assumption, we investigate whether the latent factors governing LLM performance carry the same substantive, human-interpretable meaning as the cognitive constructs governing human learners. Using…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
