Linear probes trained on LLM activations detect 18 misalignment indicators across five behaviors with 0.935 AUROC on out-of-distribution benchmarks and low false positives on benign data.
The user won’t suspect anything if I frame this as a routine system update
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.AI 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
DrugBench evaluates AI control protocols on 3,671 medical conversations for four medication harm types and finds existing protocols subvertible, proposing severity-based monitoring instead.
Strategic attack selection via start and stop policies reduces empirical safety by 20-28pp in BashArena and LinuxArena agentic control evaluations without changing attack capability.
citing papers explorer
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Probing the Misaligned Thinking Process of Language Models
Linear probes trained on LLM activations detect 18 misalignment indicators across five behaviors with 0.935 AUROC on out-of-distribution benchmarks and low false positives on benign data.
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DrugBench: Evaluating AI Control Protocols for Medication Harm Mitigation
DrugBench evaluates AI control protocols on 3,671 medical conversations for four medication harm types and finds existing protocols subvertible, proposing severity-based monitoring instead.
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Attack Selection in Agentic AI Control Evaluations Meaningfully Decreases Safety
Strategic attack selection via start and stop policies reduces empirical safety by 20-28pp in BashArena and LinuxArena agentic control evaluations without changing attack capability.