3 papers
cs.LG2025
Unlearning That Lasts: Utility-Preserving, Robust, and Almost Irreversible Forgetting in LLMs
Naman Deep Singh, Maximilian Müller, Francesco Croce +1
Unlearning in large language models (LLMs) involves precisely removing specific information from a pre-trained model. This is crucial to ensure safety of LLMs by deleting private d…
cs.RO2025
DigiT4TAF -- Bridging Physical and Digital Worlds for Future Transportation Systems
Maximilian Zipfl, Pascal Zwick, Patrick Schulz +22
In the future, mobility will be strongly shaped by the increasing use of digitalization. Not only will individual road users be highly interconnected, but also the road and associa…
astro-ph.CO2024
Be careful in multi-messenger inference of the Hubble constant: A path forward for robust inference
Michael Müller, Suvodip Mukherjee, Geoffrey Ryan
Multi-messenger observations of coalescing binary neutron stars (BNSs) are a direct probe of the expansion history of the universe and carry the potential to shed light on the disp…