Subjective Evaluation

Subjective evaluation focuses on measuring human perception and preferences, particularly in contexts where objective ground truth is lacking or insufficient. Current research emphasizes developing methods to capture individual differences in perception, often employing deep learning models (like transformers and neural networks) and incorporating multimodal data (e.g., images, text, audio) to improve the accuracy and reliability of subjective assessments. This field is crucial for advancing human-centered AI, improving the design of interactive systems, and ensuring the fairness and effectiveness of AI applications across diverse user populations.