On the generalization of language models from in-context learning and finetuning: a controlled study

Understand

Large language models exhibit exciting capabilities, yet can show surprisingly narrow generalization from finetuning.

• E.g.
• they can fail to generalize to simple reversals of relations they are trained on, or fail to make simple logical deductions based on trained information.
• These failures to generalize factual information from fine-tuning can significantly hinder the reasoning capabilities of these models.