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cs.CL2025
On the Brittleness of LLMs: A Journey around Set Membership
Lea Hergert, Gábor Berend, Mario Szegedy +2
Large language models (LLMs) achieve superhuman performance on complex reasoning tasks, yet often fail on much simpler problems, raising concerns about their reliability and interp…
cs.LG2025
No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks
Attila Szász, Balázs Bánhelyi, Márk Jelasity
The ultimate goal of verification is to guarantee the safety of deployed neural networks. Here, we claim that all the state-of-the-art verifiers we are aware of fail to reach this…