Target Refinement Objective

Target refinement, a crucial aspect of various fields from AI to robotics, focuses on improving initial outputs or predictions through iterative adjustments. Current research emphasizes developing methods to automatically identify areas needing refinement, employing techniques like reward models (e.g., outcome-based and stepwise ORMs) and leveraging feedback mechanisms to guide the refinement process. This work is significant for enhancing the accuracy and efficiency of AI models, improving the reliability of robotic systems, and enabling more effective knowledge graph management and data analysis.