33 citations · 39 across the 5 of their papers we have counts for
5 papers
Identifying good forecasters via adaptive cognitive tests
Edgar C. Merkle, Nikolay Petrov, Sophie Ma Zhu +3
Assessing forecasting performance is a time intensive activity, often requiring months or years before we know whether or not the reported forecasts were accurate. Cognitive tests…
ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities
Ezra Karger, Houtan Bastani, Chen Yueh-Han +4
Forecasts of future events are essential inputs into informed decision-making. Machine learning (ML) systems have the potential to deliver forecasts at scale, but there is no frame…
Wisdom of the Silicon Crowd: LLM Ensemble Prediction Capabilities Rival Human Crowd Accuracy
Philipp Schoenegger, Indre Tuminauskaite, Peter S. Park +1
Human forecasting accuracy in practice relies on the 'wisdom of the crowd' effect, in which predictions about future events are significantly improved by aggregating across a crowd…
AI-Augmented Predictions: LLM Assistants Improve Human Forecasting Accuracy
Philipp Schoenegger, Peter S. Park, Ezra Karger +2
Large language models (LLMs) match and sometimes exceeding human performance in many domains. This study explores the potential of LLMs to augment human judgement in a forecasting…
Probability aggregation in time-series: Dynamic hierarchical modeling of sparse expert beliefs
Ville A. Satopää, Shane T. Jensen, Barbara A. Mellers +2
Most subjective probability aggregation procedures use a single probability judgment from each expert, even though it is common for experts studying real problems to update their p…