4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2026
No More, No Less: Task Alignment in Terminal Agents
Sina Mavali, David Pape, Jonathan Evertz +5
Terminal agents are increasingly capable of executing complex, long-horizon tasks autonomously from a single user prompt. To do so, they must interpret instructions encountered in…
cs.CL2026
Unknown Unknowns: Do Hidden Intentions in LLMs Evade Detection?
Devansh Srivastav, David Pape, Lea Schönherr
LLMs expand accessibility and provide wide-reaching access to information. Yet these interactions also create opportunities to embed subtle, goal-oriented behaviours that shape wha…
cs.CR2025★ 4 cited
Chasing Shadows: Pitfalls in LLM Security Research
Jonathan Evertz, Niklas Risse, Nicolai Neuer +12
Large language models (LLMs) are increasingly prevalent in security research. Their unique characteristics, however, introduce challenges that undermine established paradigms of re…