Generalization to Other Writing Domains

Determine how well the trained reinforcement-learning models for constructive feedback on English creative stories generalize to other writing domains, such as academic or technical writing.

Background

The paper trains and evaluates reinforcement-learning policies and reward models exclusively on English creative stories. The authors note that extending the approach to other genres and languages is currently constrained by the lack of high-quality feedback annotations for those settings.

The unresolved issue is whether models trained on creative-story feedback can transfer effectively to domains with different conventions, objectives, and standards, including academic and technical writing. The question concerns empirical generalization rather than merely applying the same training procedure to new data.

References

While it thus remains an open question as to how well the trained models generalize to other writing domains, such as academic or technical writing, we expect that the general process should apply to these as well.

— Generating Constructive Feedback on Stories via Reinforcement Learning  (2609.04824 - Stahl et al., 4 Sep 2026) in Section Limitations, first limitation