# Alignment-Aware Quantization for LLM Safety

**Source:** https://arxiv.org/abs/2511.07842  
**Authors or institution:** Sunghyun Wee, Suyoung Kim, Hyeonjin Kim, Kyomin Hwang, Nojun Kwak  
**Publication date:** 2025-11-11  
**Publication status:** arXiv preprint  
**Evidence level:** Emerging evidence  
**Date last reviewed in UTC:** 2026-06-26T00:00:00Z

## Direct findings or source content

Conventional low-perplexity quantization objectives can miss safety degradation in studied models.

## Cognivirus interpretation

For Cognivirus.com, this source is used to examine risk at the level of adaptive systems, component compositions, evaluator boundaries, and behavioral persistence. The site interpretation is narrower than the source when the source is experimental, and more explicitly qualified when the source is architectural or programmatic.

## Limits

Preprint; method scope and robustness require independent replication. That all low-bit deployments are unsafe or that AAQ is sufficient in every setting.

## Source handling

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