Multimodal Reasoning Tasks
- - Multimodal reasoning: This refers to a model's ability to integrate multiple modalities of information, such as text, images, and charts, and perform cross-modal analysis and logical inference. In the context of education, it can help students connect textbook explanations with diagrams to grasp abstract concepts. In business analytics, it can help marketers forecast market trends by combining text and charts from market reports. In short, multimodal reasoning is a core competency for AI to tackle real-world complexities.
- - Olympiad-level reasoning: This evaluates models' performance regarding high-difficulty problems from competitions like the International Mathematical Olympiad (IMO). These problems require complex logical structures, multi-step derivations, and innovative thinking. They often lack a single “correct” answer, but instead test whether AI can “think outside the box” and find optimal solutions. Olympiad-level reasoning is a stringent test for determining whether a model possesses genuine “intelligence.”