hypedarhypedar
feedtrendsdiscovershowcasearchive
login
login
login
FeedTrendsDiscoverShowcaseArchiveDashboard
Submit Showcase

Trending now

Workflow + Code Generation + Automation62Agents + Optimization56Robotics + Design54
View all trends →

hypedar

AI trend radar for developers. Catch emerging papers, repos, and discussions before the hype peaks.

AboutGitHubDiscord

By the makers of hypedar

Codepawl

Open-source tools for developers.

Explore our tools →
AboutPrivacyTermsX

© 2026 Codepawl

Built by Codepawl·© 2026

About·Terms·Privacy·Security

GitHub·Discord·X

feedtrendsdiscovershowcasearchive
← feed
arXiv8h ago
5.3

CSAttention: Centroid-Scoring Attention for Accelerating LLM Inference

Chuxu Song, Zhencan Peng, Jiuqi Wei, Chuanhui Yang

View original ↗

Analysis

Viral velocity
low
Implementation gapYES
Novelty8/10
Categorypaper
Topics
inferencequantization

Opportunity Brief

Build a drop-in replacement for KV-cache attention mechanisms that uses centroid-scoring to sparsify attention at inference time. This would significantly reduce memory footprints for long-context LLM inference.

Suggested repo: fast-centroid-attn

"Accelerate your long-context LLMs without training."

Estimated effort: 100h