Safe at One Loop, Risky at Another: Aligning Safety Across Recurrent Depths in Looped Language Models
Evaluates harmful-query and jailbreak behavior at different recurrent depths of looped language models. Proposes depth-specific control, state sharing, and joint supervision to align safety behavior across depths.
First public: · Added to this list: October 18, 2026
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arXiv:2610.10625 · Initial submission: 2026-10-07
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Recurrent reasoning — Repeat parts of the model or keep intermediate information in memory while working through a problem. Some methods also learn how many passes to run.
Analysis and evaluation — Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.
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