by yecchen · Agent Tool · ★ 91
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MIRAI : Evaluating LLM Agents for Event Forecasting This repository contains the code and data for the paper "MIRAI: Evaluating LLM Agents for Event Forecasting". Authors (Equal Contribution): Chenchen Ye\, Ziniu Hu\, Yihe Deng\, Zijie Huang, Mingyu Derek Ma, Yanqiao Zhu, Wei Wang. Citation: If you find this repo useful for your research, please consider citing the paper @misc{ye2024miraievaluatingllmagents, title={MIRAI: Evaluating LLM Agents for Event Forecasting}, author={Chenchen Ye and Ziniu Hu and Yihe Deng and Zijie Huang and Mingyu Derek Ma and Yanqiao Zhu and Wei Wang}, year={2024}, e
| Stars | 91 |
| Forks | 18 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 68.3031510979497/100 |
| Last Updated | 2024-07-02 |
| Created | 2024-07-01 |
| Platforms | python |
| Est. Tokens | ~260k |
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MIRAI is Code and Data for "MIRAI: Evaluating LLM Agents for Event Forecasting". It is categorized as a Agent Tool with 91 GitHub stars.
MIRAI is primarily written in Python. It covers topics such as event-forecasting, llm, llm-agent.
You can find installation instructions and usage details in the MIRAI GitHub repository at github.com/yecchen/MIRAI. The project has 91 stars and 18 forks, indicating an active community.
The top alternatives to MIRAI on Agent Skills Hub include palico-ai, Awesome-AI-For-Security, mcp-ts-template. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.