Event forecasting is inherently influenced by multifaceted considerations, including international relations, regional historical dynamics, and cultural contexts. However, existing LLM-based approaches employ single-model architectures that generate predictions along a singular explicit trajectory, constraining their ability to capture diverse geopolitical nuances across complex regional contexts. To address this limitation, we introduce ThinkTank-ME, a novel Think Tank framework for Middle East event forecasting that emulates collaborative expert analysis in real-world strategic decision-making. To facilitate expert specialization and rigorous evaluation, we construct POLECAT-FOR-ME, a Middle East-focused event forecasting benchmark. Experimental results demonstrate the superiority of multi-expert collaboration in handling complex temporal geopolitical forecasting tasks. The code is available at https://github.com/LuminosityX/ThinkTank-ME.
Cite
@article{arxiv.2601.17065,
title = {ThinkTank-ME: A Multi-Expert Framework for Middle East Event Forecasting},
author = {Haoxuan Li and He Chang and Yunshan Ma and Yi Bin and Yang Yang and See-Kiong Ng and Tat-Seng Chua},
journal= {arXiv preprint arXiv:2601.17065},
year = {2026}
}