MM-PhyQA: Multimodal Physics Question-Answering With Multi-Image CoT Prompting

arXiv:2404.08704v1 Announce Type: new
Abstract: While Large Language Models (LLMs) can achieve human-level performance in various tasks, they continue to face challenges when it comes to effectively tackling multi-step physics reasoning tasks. To identify the shortcomings of existing models and facilitate further research in this area, we curated a novel dataset, MM-PhyQA, which comprises well-constructed, high schoollevel multimodal physics problems. By evaluating the performance of contemporary LLMs that are publicly available, both with and without the incorporation of multimodal elements …

abstract arxiv challenges cs.ai cs.cl dataset face human identify image language language models large language large language models llms multimodal novel performance physics prompting question reasoning research tasks type