Query Validation And Error Correction With User Feedback Loop

via “corrective re-prompting with iterative refinement”

Adding guardrails to large language models.

Unique: Implements a stateful correction loop that preserves conversation context across retries, allowing the LLM to learn from previous failures within the same session and apply cumulative corrections rather than starting fresh each time

vs others: More sophisticated than simple retry-with-backoff because it provides semantic feedback about validation failures rather than blind retries, increasing success rates for complex outputs