arxiv
PublishedMay 26, 2026 at 4:00 AM
—neutral
VectorArk: Learning Practical Image Vectorization with Rounded Polygon Representation
Publisher summary· verbatim
arXiv:2605.24398v1 Announce Type: cross Abstract: Recent vision-language model (VLM)-based approaches have achieved impressive results on image vectorization tasks. However, they are typically evaluated on synthetic benchmarks, where clean SVGs are rasterized at high resolution and then re-vectorize
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivFederatedSkill: Federated Learning for Agentic Skill Evolution3harxivChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning3harxivThinking Past the Answer: Evaluating Harmful Overthinking in Large Reasoning Models3harxivToward a Modular Architecture for Embedded AI Agent Systems at the Edge3hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗