EQMs, sixty LLM-scored reasoning patterns, predict forecast accuracy at both item and person levels and outperform prior text-analysis methods in a large pre-registered tournament dataset.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
InfoDelphi partitions evidence to induce information asymmetry in multi-agent LLM deliberation, yielding 12-18% Brier score gains and 4-8 pp accuracy gains on a 375-question benchmark.
citing papers explorer
-
Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments
EQMs, sixty LLM-scored reasoning patterns, predict forecast accuracy at both item and person levels and outperform prior text-analysis methods in a large pre-registered tournament dataset.