Evaluating Strategic Reasoning in Forecasting Agents
Forecasting benchmarks produce accuracy leaderboards but little insight into why some forecasters are more accurate than others. We introduce Bench to the Future 2 (BTF-2), 1,417 pastcasting questions with a frozen 15M-document research corpus in which agents reproducibly research and forecast offline, producing full reasoning traces. BTF-2 detects accuracy differences of 0.004 Brier score, and can distinguish differential agent strengths in research vs. judgment. We build a forecaster 0.011 Brier more accurate than any single frontier agent, and use it to evaluate agent strategic reasoning without hindsight bias. We find the better forecaster differs primarily in its pre-mortem analysis ...
| Authors | Tom Liptay, Dan Schwarz, Rafael Poyiadzi et al. |
|---|---|
| Primary category | cs.AI |
| Published | 28 April 2026 |
| Last updated at source | 28 April 2026 |
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