OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich Image Reasoning

Understand

Recent advancements in multimodal slow-thinking systems have demonstrated remarkable performance across various visual reasoning tasks.

• However, their capabilities in text-rich image reasoning tasks remain understudied due to the absence of a dedicated and systematic benchmark.
• To address this gap, we propose OCR-Reasoning, a novel benchmark designed to systematically assess Multimodal Large Language Models on text-rich image reasoning tasks.
• Specifically, OCR-Reasoning comprises 1,069 human-annotated examples spanning 6 core reasoning abilities and 18 practical reasoning tasks in text-rich visual scenarios.