Papers with self-correction loop

1 papers
InteracSPARQL : An Interactive System for SPARQL Query Refinement Using Natural Language Explanations (2026.findings-acl)

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Challenge: Existing approaches for SPARQL generation rely on one-turn models.
Approach: They propose a training-free interactive refinement pipeline that acts as a plug-and-play enhancement for existing SPARQL systems.
Outcome: The proposed approach improves the accuracy of base models without fine-tuning . it transforms potentially flawed queries from any source into verifiable code .

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