# Ablation, Statistical Inference, and Validation for KV-Cache Compression

> Source: <https://arxiv.org/abs/2607.09683>
> Published: 2026-07-14 04:00:00+00:00

# Computer Science > Machine Learning

[Submitted on 14 Jun 2026]

# Title:Ablation, Statistical Inference, and Validation for KV-Cache Compression

[View PDF](/pdf/2607.09683)

[HTML (experimental)](https://arxiv.org/html/2607.09683v1)

Abstract:This study systematically compares Turbo-Quant and SpectralQuant KV-cache compression, evaluating non-dominated schemes, including WHT rotation with Beta Lloyd-Max and QJL, through a statistical validation methodology that separates systematic codec differences from implementation variance. Key findings reveal that while eigenbasis-based methods fail on heavy-tailed data due to covariance instability, they excel in structured regimes, with the effective semantic dimension ($d_{eff}$) adapting to calibration budgets rather than true data rank. (this is an abstract of the abstract thank you )

### Current browse context:

cs.LG

### References & Citations

Loading...

# Bibliographic and Citation Tools

Bibliographic Explorer

*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))
Connected Papers

*(*[What is Connected Papers?](https://www.connectedpapers.com/about))
Litmaps

*(*[What is Litmaps?](https://www.litmaps.co/))
scite Smart Citations

*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article

alphaXiv

*(*[What is alphaXiv?](https://alphaxiv.org/))
CatalyzeX Code Finder for Papers

*(*[What is CatalyzeX?](https://www.catalyzex.com))
DagsHub

*(*[What is DagsHub?](https://dagshub.com/))
Gotit.pub

*(*[What is GotitPub?](http://gotit.pub/faq))
Hugging Face

*(*[What is Huggingface?](https://huggingface.co/huggingface))
ScienceCast

*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos

# Recommenders and Search Tools

Influence Flower

*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))
CORE Recommender

*(*[What is CORE?](https://core.ac.uk/services/recommender))
IArxiv Recommender

*(*[What is IArxiv?](https://iarxiv.org/about))# arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).