Quantization’s New Twist: Mass Diffusion for More Efficient AI

A novel framework optimizes the compression of large language models by strategically reordering data before quantization, dramatically improving accuracy and reducing computational costs.

![Semantic caching vulnerabilities arise when distinct requests, such as [latex]A_1[/latex] (attacker) and [latex]P_1[/latex] (victim), unexpectedly resolve to the same semantic key [latex]K_1[/latex], enabling the attacker to hijack the victim’s response.](https://arxiv.org/html/2601.23088v1/x1.png)

