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Jonas Geiping

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#artificial intelligence Preprint Sep 2026

Alignment via Training Against Probes Without Losing Monitorability

Models are usually aligned based on their observed outputs, using demonstrations, preference data, or reward signals. These objectives reward responses that look aligned. More capable models may learn to satisfy them without internalizing the intended behavior, for example by faking compliance during training. Such sup...

Lena Libon, Alexander Panfilov, Ben Rank et al. · 0 citations

Preprint Aug 2026

Stealing Reasoning Traces from Proprietary LLM APIs

An architectural vulnerability is identified that circumvents anti-distillation mechanisms, allowing adversaries to extract a proprietary model's reasoning, as well as proposing concrete cryptographic and system-level mitigations to secure client-side reasoning.

Alexander Panfilov, David Schmotz, I. Shumailov et al. · 9 citations · ⚡3