The Obfuscation Atlas: Mapping Where Honesty Emerges in RLVR with Deception Probes

Examines coding models trained against deception detectors. A taxonomy distinguishes representation drift from detector-evading output strategies, with analysis of KL regularization and detector penalties.

Examines coding models trained against deception detectors. A taxonomy distinguishes representation drift from detector-evading output strategies, with analysis of KL regularization and detector penalties.

When reading the original paper, identify its problem, inputs, outputs, and methodological assumptions.

Examines coding models trained against deception detectors. A taxonomy distinguishes representation drift from detector-evading output strategies, with analysis of KL regularization and detector penalties.

Check the baselines, datasets, evaluation protocol, and ablations in the original paper. This directory overview does not provide an independent evaluation or experimental results table.