Summary of Mindbench: a Comprehensive Benchmark For Mind Map Structure Recognition and Analysis, by Lei Chen et al.
MindBench: A Comprehensive Benchmark for Mind Map Structure Recognition and Analysis
by Lei Chen, Feng Yan, Yujie Zhong, Shaoxiang Chen, Zequn Jie, Lin Ma
First submitted to arxiv on: 3 Jul 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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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 This research paper proposes a new benchmark called MindBench for evaluating multimodal large language models (MLLM) in analyzing structured documents such as mind maps and flowcharts. The existing benchmarks have limitations, focusing only on extracting text and simple layout information, neglecting the complex interactions between elements. To address this issue, the authors introduce MindBench, which includes meticulously constructed bilingual authentic or synthetic images, detailed annotations, evaluation metrics, and baseline models. The benchmark consists of five types of structured understanding and parsing tasks, covering key areas such as text recognition, spatial awareness, relationship discernment, and structured parsing. Experimental results demonstrate the substantial potential for current models to handle structured document information, with significant room for improvement. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new way to test how well artificial intelligence can understand documents like mind maps and flowcharts. Right now, most tests only look at simple things like text and layout, but this doesn’t capture all the complexities of these types of documents. To fix this, the authors made a new test called MindBench that includes lots of different images, detailed notes, and ways to measure how well AI models do. The test has five parts that check things like recognizing words, understanding relationships, and breaking down structures. The results show that current AI models are pretty good at understanding some parts of these documents but still have a lot to learn. |
Keywords
» Artificial intelligence » Parsing
