ForecastBench: Dynamic LLM Forecasting Benchmark
webForecastBench is a dynamic benchmark measuring LLM forecasting accuracy against human baselines, relevant to AI safety as forecasting ability serves as a proxy for general intelligence and helps track AI capability progress toward and beyond human-level performance.
Metadata
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Summary
ForecastBench is a contamination-free benchmark that evaluates LLM forecasting accuracy against human comparison groups, including superforecasters. It maintains both a baseline leaderboard (no tools) and a tournament leaderboard (with scaffolding/tools), and projects when LLMs will reach superforecaster-level performance.
Key Points
- •Dynamic, contamination-free benchmark preventing LLMs from training on benchmark questions, ensuring valid capability measurement.
- •Compares LLM forecasting performance against human baselines including superforecasters as a proxy for general intelligence.
- •Dual leaderboards: baseline (raw model performance) and tournament (with tool use, fine-tuning, ensembling).
- •Tracks historical progress in LLM forecasting capabilities and projects date of LLM-superforecaster parity.
- •Open to public submissions, enabling broad participation in capability evaluation.
Cited by 2 pages
| Page | Type | Quality |
|---|---|---|
| Forecasting Research Institute (FRI) | Organization | 55.0 |
| ForecastBench | Project | 53.0 |
1 FactBase fact citing this source
| Entity | Property | Value | As Of |
|---|---|---|---|
| ForecastBench | Founded Date | Sep 2024 | — |
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Tournament leaderboard
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