Paper Discussion: Why Do Larger Language Models Learn More?

Why do larger language models consistently outperform smaller ones? Is it simply because they have more parameters, or is there a deeper reason behind the remarkable success of scaling?

In this meetup, we'll discuss the recent paper "Why Larger Models Learn More" (arXiv:2605.29548), which proposes a new theoretical perspective on one of the most fundamental questions in modern AI: why increasing model size leads to better learning and stronger generalization.

Rather than focusing on scaling laws themselves, the paper asks what changes inside the learning process as models become larger, and offers a framework for understanding why larger models are able to acquire more knowledge from the same data.