SOURCE-LINKED INTELLIGENCE
SciMIF: Understanding Multimodal Instruction Following in Scientific Domains
Understanding instruction-following capabilities in scientific domains is essential for effectively leveraging Multimodal Large Language Models (MLLMs) to advance the development of scientific fields. In this work, we introduce SciMIF, a novel benchmark designed to evaluate the capability of MLLMs in following complex scientific instructions. Specifically, based on an extensive analysis of 22 distinct tasks across 5 representative scientific disciplines, we propose a comprehensive taxonomy comprising 10 constraint groups that captures both general functional requirements and discipline-specifi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T16:30:20.000Z
First collected: 2026-09-21T09:11:58.312Z. This is not the publication date.