LLM-Based Auto Correction

The use of large language models to automatically detect and correct common text errors without requiring manual user intervention. In accessibility contexts, LLM-based auto correction can reduce the editing burden for users with disabilities by fixing predictable errors (grammar, spelling, common substitutions) that would otherwise require multiple interaction steps to correct manually. While promising, research shows that users may be slow to adopt AI-assisted correction features, preferring manual control until they build trust in the system accuracy.