| license: cc-by-sa-4.0 | |
| language: | |
| - en | |
| pretty_name: ForecastBench | |
| [](https://iclr.cc/virtual/2025/poster/28507) [](https://arxiv.org/abs/2409.19839) | |
| ## ForecastBench Datasets | |
| This repository contains the datasets produced by ForecastBench, a forecasting benchmark for | |
| LLMs. | |
| More info at [https://www.forecastbench.org](https://www.forecastbench.org/). | |
| Code available at [https://github.com/forecastingresearch/forecastbench](https://github.com/forecastingresearch/forecastbench). | |
| ## License | |
| The datasets in this repository are distributed under the [CC BY-SA 4.0 license](https://creativecommons.org/licenses/by-sa/4.0/legalcode). | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{karger2025forecastbench, | |
| title={ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities}, | |
| author={Ezra Karger and Houtan Bastani and Chen Yueh-Han and Zachary Jacobs and Danny Halawi and Fred Zhang and Philip E. Tetlock}, | |
| year={2025}, | |
| booktitle={International Conference on Learning Representations (ICLR)}, | |
| url={https://iclr.cc/virtual/2025/poster/28507} | |
| } | |
| ``` | |