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20152026
most citedExplaining Deep Neural Networks and Beyond: A Review of Methods and Applications

1.5k citations · 5.3k across the 82 of their papers we have counts for

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91 papers

cs.AI2026

Chain of Thought Monitoring Can Fail Even When CoT Is Necessary

Lennart Bürger, Piotr Komorowski, Moritz Weckbecker +4

Chain of Thought (CoT) monitoring is used by frontier labs to detect misbehaviour of AI systems. Yet, its reliability remains poorly understood. We attribute this to the lack of a…

cs.CL2026

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

Maximilian von Klinski, Sebastian Lapuschkin, Wojciech Samek +1

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 LL…

cs.AI2026

Can Data Attribution Filter Out Subliminal Learning? Not Reliably

Moritz Weckbecker, Sweta Jena, Jonas Müller +5

Subliminal learning allows language models to transmit behavioral traits through training data with no obvious semantic relationship to those traits, undermining content-based data…

cs.CV2026

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

Jim Berend, Reduan Achtibat, Daniel Schäffer +4

Vision Transformers (ViTs) are central to most modern vision models, yet obtaining input attributions that are fine-grained, faithful, and stable remains challenging. Layer-wise Re…

cs.AI2026

Safety Signals to Verify NetOps Agents with Action-Level Granularity

Tobias Labarta, Frederik Pahde, Novak Boškov +6

Agentic Network Operations (NetOps) are an emerging paradigm promising to enable workload-aware, self-adjustable, and reliable autonomous networks. While agents have proven their v…

cs.CV2026

Concept-based explanation of gene expression prediction from H&E images

Amos Muench, Jonathan Thielmann, Reduan Achtibat +9

Recent advances in pathology foundation models have enabled accurate prediction of spatial transcriptomics (ST) from routine H&E images. However, existing explainability methods fo…