Summary of Mathverse: Does Your Multi-modal Llm Truly See the Diagrams in Visual Math Problems?, by Renrui Zhang et al.
MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
by Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Peng Gao, Hongsheng Li
First submitted to arxiv on: 21 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces MathVerse, a novel visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in deducing answers from textual questions with diagrams. The authors create 15K test samples by transforming 2,612 high-quality math problems into six versions each, offering varying degrees of information content in multi-modality. This allows for a comprehensive assessment of whether MLLMs can truly understand visual diagrams for mathematical reasoning. A Chain-of-Thought (CoT) evaluation strategy is proposed to fine-grade the output answers by adaptively extracting crucial reasoning steps and scoring them with detailed error analysis. The authors hope MathVerse will guide the future development of MLLMs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MathVerse is a new benchmark that helps us understand if big language models can really solve math problems by looking at pictures. Right now, these models are great at answering questions about text, but not so good at using diagrams to figure out answers. The researchers created 15,000 test samples from 2,600 math problems with different amounts of information in each sample. This will help us see if the models can really understand what they’re looking at and make smart decisions. |
Keywords
* Artificial intelligence * Multi modal
