2026
Human-Corrected Labels Learning: Enhancing Labels Quality via Human Correction of VLMs Discrepancies
AAAI 2026technical
Vision-Language Models (VLMs), with their powerful content generation capabilities, have been successfully applied to data annotation processes. However, the VLM-generated labels exhibit dual limitations: low quality (i.e., label noise) and absence of error correction mechanisms. To enhance label qu