Evaluability of latent-space reasoning

Develop mature, standardized supervision and evaluation protocols for latent-space reasoning in large language models that enable process-level verification of latent trajectories and permit fair, comparable assessment across tasks, datasets, and metrics.

Background

The survey argues that latent reasoning trajectories are not directly observable, which hampers process-level verification and makes it difficult to determine whether intermediate computations are correct or relevant. Existing evaluations largely rely on final-answer accuracy or post hoc verbalization, providing only indirect evidence about the latent process.

The authors note that current benchmarking efforts are fragmented and that widely accepted protocols for supervision and evaluation are lacking, creating barriers to fair comparisons and cumulative progress in the field.