hypedarhypedar
feedtrendsdiscovershowcasearchive
login
login
login
FeedTrendsDiscoverShowcaseArchiveDashboard
Submit Showcase

Trending now

Privacy + Training + Agents67Inference + Agents + Llm67Math + Games56
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
arXiv9h ago
4.3

The Cost of Relaxation: Evaluating the Error in Convex Neural Network Verification

Merkouris Papamichail, Konstantinos Varsos, Giorgos Flouris, Jo\~ao Marques-Silva

View original ↗

Analysis

Viral velocity
low
Implementation gapYES
Novelty5/10
Categorypaper
Topics
verificationneural-networks

Opportunity Brief

Create a diagnostic tool that visualizes the divergence caused by convex relaxation in NN verification. This helps safety researchers debug why their verifiers might yield loose bounds.

Suggested repo: relax-check

"Know exactly when your neural network verifier is lying to you."

Estimated effort: 40h