Alignment-Aware Quantization for LLM Safety

Evidence card

Claim

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

Evidence level

Emerging evidence

Source

https://arxiv.org/abs/2511.07842

Publication date

2025-11-11

Authors or institution

Sunghyun Wee, Suyoung Kim, Hyeonjin Kim, Kyomin Hwang, Nojun Kwak

System tested

Post-training quantization with alignment-preserving contrastive loss across LLaMA, Qwen, and Mistral families as reported.

Limitations

Preprint; method scope and robustness require independent replication.

What the evidence does show

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

What the evidence does not show

That all low-bit deployments are unsafe or that AAQ is sufficient in every setting.

Date last reviewed in UTC

2026-06-26T00:00:00Z