activity
20242026
collaborators

7 papers

cs.LG2026

Discovering Subgroups with Exceptional Survival Characteristics

Mhd Jawad Al Rahwanji, Sascha Xu, Nils Philipp Walter +1

In many applications, it is important to identify subpopulations that survive longer or shorter than the rest of the population. In medicine, for example, it allows determining whi…

cs.CV2026

Hidden in Plain Sight -- Class Competition Focuses Attribution Maps

Nils Philipp Walter, Jilles Vreeken, Jonas Fischer

Attribution methods reveal which input features a neural network uses for a prediction, adding transparency to their decisions. A common problem is that these attributions seem uns…

cs.CR2026

Soft Instruction De-escalation Defense

Nils Philipp Walter, Chawin Sitawarin, Jamie Hayes +2

Large Language Models (LLMs) are increasingly deployed in agentic systems that interact with an external environment; this makes them susceptible to prompt injections when dealing…

cs.LG2025

Can LLMs subtract numbers?

Mayank Jobanputra, Nils Philipp Walter, Maitrey Mehta +7

We present a systematic study of subtraction in large language models (LLMs). While prior benchmarks emphasize addition and multiplication, subtraction has received comparatively l…

cs.LG2025

When Flatness Does (Not) Guarantee Adversarial Robustness

Nils Philipp Walter, Linara Adilova, Jilles Vreeken +1

Despite their empirical success, neural networks remain vulnerable to small, adversarial perturbations. A longstanding hypothesis suggests that flat minima, regions of low curvatur…

cs.LG2025

The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective

Nils Philipp Walter, Linara Adilova, Jilles Vreeken +1

Flatness of the loss surface not only correlates positively with generalization, but is also related to adversarial robustness since perturbations of inputs relate non-linearly to…