The “Super Weight:” How Even a Single Parameter can Determine a Large Language Model’s Behavior

A recent paper from Apple researchers, “The Super Weight in Large Language Models,” reveals that an extremely small subset of parameters in LLMs (in some cases, a single parameter) can exert a disproportionate influence on an LLM’s overall functionality (see Figure 1). This work highlights the critical role of these “super weights” and their corresponding “super activations,” offering a new insight into LLM architecture and avenues for efficient model compression. The paper provides full technical details and experimental results; in this post, we provide a high-level overview of the key…