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Research Blog

Welcome to our research blog, where we highlight the work and achievements of our researchers, with a special focus on our Junior Members. Here, you’ll gain insight into their innovative work and the fresh ideas they bring to the dynamic fields of ML and AI.

Link to Foundations of Diffusion: One Map for Images and Text

05.03.2026

Foundations of Diffusion: One Map for Images and Text

MCML Research Insight – With Vincent Pauline, Tobias Höppe, Andrea Dittadi, and Stefan Bauer

From hyper-realistic video generation to protein design, Diffusion Models are the engine behind the current wave of Generative AI. But if you try to understand how diffusion models actually work, you …

Link to COSMOS – Teaching Vision-Language Models to Look Beyond the Obvious

19.02.2026

COSMOS – Teaching Vision-Language Models to Look Beyond the Obvious

MCML Research Insight - With Sanghwan Kim, Rui Xiao, Mariana-Iuliana Georgescu, Stephan Alaniz, and Zeynep Akata

Today’s AI systems are remarkably good at recognizing what stands out most. Yet understanding how details relate to each other remains surprisingly difficult. Imagine asking an AI assistant to …

Link to Needle in a Haystack: Finding Exact Moments in Long Videos

05.02.2026

Needle in a Haystack: Finding Exact Moments in Long Videos

MCML Research Insight - With With Tanveer Hannan and Thomas Seidl

Long videos are everywhere, with footage of movies, YouTube videos, body-cam recordings, and AR/VR often running for tens of minutes or even hours. Now imagine asking a simple question like “Where are …

Link to How Machines Can Discover Hidden Rules Without Supervision

29.01.2026

How Machines Can Discover Hidden Rules Without Supervision

MCML Research Insight - With Tobias Schmidt, and Steffen Schneider

How can machines learn the hidden rules that govern how systems change—how objects move, how weather patterns unfold, or how biological signals evolve—without ever being told what those rules are?

Link to From Global to Regional Explanations: Understanding Models More Locally

22.01.2026

From Global to Regional Explanations: Understanding Models More Locally

MCML Research Insight - With Giuseppe Casalicchio, Thomas Nagler, and Bernd Bischl

Machine learning models can be powerful, but understanding why they behave the way they do is often much harder. Early global interpretability tools were designed to show how each feature affects the …

Link to Research Stay at University of St. Gallen

22.01.2026

Research Stay at University of St. Gallen

Andrea Maldonado – Funded by the MCML AI X-Change Program

Between Freudenberg – “happiness mountain” – and Rosenberg – “roses mountain”, I had the pleasure to visit the Institute of Computer Science (ICS-HSG) at the University of St. Gallen (HSG) in …

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