arxiv
PublishedJune 2, 2026 at 4:00 AM
WaterSearch: Exploring Seed Pooling for Improving the Quality-Detectability Trade-off in LLM Watermarking
Publisher summary· verbatim
arXiv:2512.00837v3 Announce Type: replace Abstract: Watermarking acts as a critical safeguard in text generated by Large Language Models (LLMs). By embedding identifiable signals into model outputs, watermarking enables reliable attribution and enhances the security of machine-generated content. Exi
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
arxivSFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning18harxivOptical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning18harxivDynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models18harxivTemporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents18hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗