Experiments by Huang et al. (2024) showed that naively applying self-correction leads to worse performance and external feedback is needed for models to self improve, which can be based on matching ground truths, heuristics and task-specific metrics, unit tests results for coding questions (Shinn, et al. 2023), a stronger model (Zhang et al. 2024), as well as human feedback (Liu et al. 2023).