Home  | News

20.01.2025

Teaser image to Sarah Ball's Research Featured on on the LLM Cybersecurity podcast

Sarah Ball's Research Featured on on the LLM Cybersecurity Podcast

Understanding Jailbreak Success: A Study of Latent Space Dynamics in Large Language Models

We are happy to share that Junior Member Sarah Ball, a PhD student in the group of our PI Frauke Kreuter, has had her research featured on the LLM Cybersecurity podcast by Ariel Fogel and Tyler Bettilyon.

The discussion centered around Sarah's paper "Understanding Jailbreak Success: A Study of Latent Space Dynamics in Large Language Models" highlighting its insights and implications for the field of AI and cybersecurity.

#media #podcast #research #kreuter
Subscribe to RSS News feed

Related

Link to

02.01.2026

MCML Researchers in Highly-Ranked Journals

We are excited to announce that MCML researchers have three papers published in highly-ranked journals in %!s().

Link to "See, Don’t Assume": Revealing and Reducing Gender Bias in AI

18.12.2025

"See, Don’t Assume": Revealing and Reducing Gender Bias in AI

ICLR 2025 research led by Zeynep Akata’s team reveals and reduces gender bias in popular vision-language AI models.

Link to Fabian Theis Featured in Handelsblatt on the Future of AI in Precision Medicine

16.12.2025

Fabian Theis Featured in Handelsblatt on the Future of AI in Precision Medicine

MCML PI Fabian Theis discusses AI-driven precision medicine and its growing impact on individualized healthcare and biomedical research.

Link to Gitta Kutyniok Featured in VDI Nachrichten on AI Ethics

16.12.2025

Gitta Kutyniok Featured in VDI Nachrichten on AI Ethics

Gitta Kutyniok discusses measurable criteria for ethical AI, promoting safe and responsible autonomous decision-making.

Link to Hinrich Schütze Featured in WirtschaftsWoche on Innovative AI Approaches

16.12.2025

Hinrich Schütze Featured in WirtschaftsWoche on Innovative AI Approaches

Hinrich Schütze discusses Giotto.ai’s efficient AI models, highlighting memory separation and context-aware decoding to improve robustness.

Back to Top