Research Blog
15.01.2026
Blind Matching – Aligning Images and Text Without Training or Labels
MCML Research Insight - With Dominik Schnaus, Nikita Araslanov, and Daniel Cremers
Vision-language models have shown that images and text can live in a shared space: a picture of a “cat” often lands close to the word “cat” in the embedding space. But such models learn this correspondence because they have seen millions of image–caption pairs. What if we had …
08.01.2026
High-Res Images, Less Wait: A Simple Flow for Image Generation
MCML Research Insight - With Johannes Schusterbauer, Pingchuan Ma, Vincent Tao Hu, and Björn Ommer
Image generation models today can create almost anything, like a futuristic city glowing at sunset, a classical painting of your cat, or a realistic spaceship made of glass. But when you ask them to go bigger and sharper, the magic slows down. The process takes longer, eats up more memory, and …
18.12.2025
“See, Don’t Assume”: Revealing and Reducing Gender Bias in AI
MCML Research Insight - With Leander Girrbach, Yiran Huang, Stephan Alaniz and Zeynep Akata
Using AI and LLMs at work feels almost unavoidable today: they make things easier, but they can also go wrong in important ways. One of the trickiest problems? Gender bias. For example, if you ask about someone’s skills from a photo, it may confidently label them a “born leader” or “working well under pressure” with no real …