arxiv
PublishedJune 10, 2026 at 4:00 AM
—neutral
Alignment Collapse Under KV Cache Quantization: Diagnosis and Mitigation
Publisher summary· verbatim
arXiv:2606.09864v1 Announce Type: cross Abstract: Key-value (KV) cache quantization is widely used to reduce Large Language Model (LLM) inference memory, yet existing evaluations solely focus on measuring perplexity and accuracy without assessing the safety impact. In this study, we explore alignmen
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivWhen Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems10harxivQuery-Driven Learning for Lifted Reasoning10harxivThe Social World Model Evaluation Gap10harxivConviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models10hThe Bubble Brief
MON · WED · FRIRead quantization insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗