Summary of Visscience: An Extensive Benchmark For Evaluating K12 Educational Multi-modal Scientific Reasoning, by Zhihuan Jiang et al.
VisScience: An Extensive Benchmark for Evaluating K12 Educational Multi-modal Scientific Reasoning
by Zhihuan Jiang, Zhen Yang, Jinhao Chen, Zhengxiao Du, Weihan Wang, Bin Xu, Jie Tang
First submitted to arxiv on: 10 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: 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 The paper presents a comprehensive benchmark called VisScience to evaluate the performance of multi-modal large language models (MLLMs) in scientific reasoning across three disciplines: mathematics, physics, and chemistry. The benchmark consists of 3,000 questions drawn from K12 education, equally distributed across the three disciplines, with 1,000 questions per discipline. The questions span 21 distinct subjects and are categorized into five difficulty levels, offering a broad spectrum of topics within each discipline. The authors use VisScience to assess the performance of 25 representative MLLMs in scientific reasoning, finding that closed-source MLLMs generally outperform open-source models. The best-performing models include Claude3.5-Sonnet for mathematics, GPT-4o for physics, and Gemini-1.5-Pro for chemistry. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new benchmark called VisScience to test how well computers can understand science questions in different subjects like math, physics, and chemistry. The benchmark has 3,000 questions from elementary school to high school, divided into three disciplines. The authors tested 25 computer models on these questions and found that some models were better at answering certain types of questions than others. |
Keywords
» Artificial intelligence » Gemini » Gpt » Multi modal
