Learning to Prefer Reliably: Error-Augmented Emotion Preference Optimization with Calibrated Fusion
Experiments on the MER2026-EmoPrefer Challenge dataset and the error-augmented dataset demonstrate that EAPO improves emotion preference prediction and enhances the robustness of MLLM judges when evaluating fluent descriptions that conflict with the video's multimodal emotional evidence.