Skill 详情
scientific-llm-benchmarks
Useful for evaluating scientific ML systems, not general DS workflows.
使用前先检查
自动化审核只检查相关性,不代表安全审查或推荐。使用前请阅读来源中的说明。
SKILL.md
这段内容是审核时保存的快照。外部来源才是完整且最新的版本。
--- name: scientific-llm-benchmarks description: "A comprehensive reference of benchmarks for evaluating large language models on scientific reasoning and discovery." compatibility: ">" allowed-tools: Bash Read Write Edit Glob Grep WebFetch metadata: tags: scientific-llm-benchmarks, llm-benchmarks, science-llms, evaluation, awesome-list, reasoning, discovery, stem version: 1.0.0 source: "https://github.com/subinium/Awesome-Scientific-LLM-Benchmarks" license: MIT --- # Scientific LLM Benchmarks This skill provides references to benchmarks used for evaluating large language models on scientific reasoning and discovery. The data comes from the Awesome-Scientific-LLM-Benchmarks repository. ## Contents The complete benchmark list is stored locally within this skill: - **References List:** `references/benchmarks.md` - **Data (YAML format):** `data/benchmarks.yaml` ## Benchmark Domains Covered - **General / Multi-domain Science:** Cross-disciplinary STEM reasoning benchmarks. - **Mathematics:** Arithmetic, competition, olympiad, and frontier / formal-proof mathematics. - **Physics and Astronomy:** Physics olympiad, graduate physics, computational physics, and astronomy. - **Chemistry:** Molecular property, reaction, retrosynthesis, safety, and chemical knowledge. - **Materials Science:** Crystals, materials property prediction, and materials-science knowledge. - **Biology and Life Sciences:** Genomics, proteins, bioinformatics agents, protocols, and research biology. - **Agentic Science and AI Research:** LLM agents that write research code, run data analyses, attempt autonomous discovery, and conduct ML/AI research. ## Helper Scripts Also included are python scripts inside `scripts/`: - `generate_readme.py`: Regenerates the markdown tables and list from `data/benchmarks.yaml`. - `fetch_examples.py`: Fetches real sample rows from HuggingFace dataset URLs specified in the dataset metadata.在 GitHub 阅读完整来源 (打开外部页面)