Author

Hadas Orgad

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#artificial intelligence Preprint Sep 2026

When Models Don't Manipulate Manifolds: The Geometry of a Comparison Task

This work characterize precisely the geometry of computation in a number-comparison task, as an abstraction of comparison for decision making, and how models utilize geometry in an elegant fashion to implement it, demonstrating that the manifold hypothesis can co-exist with linear representations.

Sai Sumedh R. Hindupur, Hadas Orgad, Thomas Fel et al. · 0 citations

#natural language process... Preprint Apr 2026

A Robust Evaluation of Probe Robustness: Lessons for Reliable OOD Uncertainty Quantification

ProbeDrift is introduced, a systematic evaluation framework for supervised uncertainty probes covering a wide range of OOD settings across models, tasks, and distributional shifts, and it is argued that robust uncertainty estimation requires robust evaluation.

Joe Stacey, Hadas Orgad, Kentaro Inui et al. · 0 citations