Author

S. Lapuschkin

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#artificial intelligence Review Sep 2026

Stress-Testing LLM Lie Detectors: Role-Play Failures and Spurious Correlations

Lie detection probes aim to predict from a language model's internal states whether its output is truthful or dishonest. However, role-play complicates what"truth"means for an LLM: language models can adopt a wide range of personas that take very different claims to be true, including personas whose beliefs clearly con...

Maximilian von Klinski, S. Lapuschkin, Wojciech Samek et al. · 0 citations

#artificial intelligence Preprint Sep 2026

ResLRP: The Role of Residual Cancellation in Attribution Instability in Vision Transformers

Residual-aware Layer-wise Relevance Propagation (ResLRP) is introduced, a simple extension of LRP whose propagation rules explicitly account for cancellations in residual branches, are exactly conservative, and provably bound relevance explosion.

Jim Berend, Reduan Achtibat, Daniel Schäffer et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Safety Signals to Verify NetOps Agents with Action-Level Granularity

Agentic Network Operations (NetOps) are an emerging paradigm promising to enable workload-aware, self-adjustable, and reliable autonomous networks. While agents have proven their value in incident summarization and telemetry signal extraction, their effectiveness as autonomous control-loop engines heavily relies on the...

T. Labarta, Frederik Pahde, Novak Boškov et al. · 0 citations