A Robust Evaluation of Probe Robustness: Lessons for Reliable OOD Uncertainty Quantification
Recent work has shown that the hidden states of large language models contain signals useful for uncertainty estimation, motivating a growing interest in efficient probe-based approaches. Yet it remains unclear how robust existing methods are, with prior work reporting conflicting conclusions under substantially different evaluation settings. We address this by introducing ProbeDrift, a systematic evaluation framework for supervised uncertainty probes covering a wide range of OOD settings across models, tasks, and distributional shifts. Using ProbeDrift, we train over 2,000 probes to disentangle the effect of key design choices, showing poor robustness of current methods beyond near-OOD s...
| Authors | Joe Stacey, Hadas Orgad, Kentaro Inui et al. |
|---|---|
| Primary category | cs.CL |
| Published | 13 April 2026 |
| Last updated at source | 30 August 2026 |
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