OracleZoom Combines On-Policy Self-Distillation and Reference Constraints to Cut Hallucinations in Extreme Super-Resolution
Shubhashis Roy Dipta · hf · 2026-09-10
OracleZoom, released on Hugging Face, tackles recursive image super-resolution at extreme magnifications. The method combines trajectory-based training with cross-scale supervision and a latent prior, constrained by reference signals, to reduce hallucinations that typically appear at high zoom factors. Inspired by on-policy self-distillation, it aims for more faithful high-resolution outputs.
More from Multimodal
- Magnific teases October 28 release: 'We're making it move' — cuenca · 2026-10-27
- Midjourney --sref demo: retro Americana Batman art series — gizakdag · 2026-10-27
- AI video is a new medium, not cinema or animation — and it's perfect for depicting dreams — Kyrannio · 2026-10-27
- Dad turns his toddler's 31-year-old quote into a song via SUNO kids' choir — NathanpmYoung · 2026-10-27
- Band's local-AI music video hits 200k views: 900 generations kept 64, 3-second clips beat face drift — Hwang0500 · 2026-10-27
- Adobe Firefly video editor walkthrough: one-sentence Quick Cut turns 32s into 20s — LudovicCreator · 2026-10-26