Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing

ArXi:2601.15356v4 Announce Type: replace-cross Reinforcement Learning (RL) has empowered Multimodal Large Language Models (MLLMs) to achieve superior human preference alignment in Image Quality Assessment (IQA). However, existing RL-based IQA models typically rely on coarse-grained global views, failing to capture subtle local degradations in high-resolution scenarios.