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cs.CL2026
Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments
Christopher W. Karvetski, Sheldon S. Huang, Simas KuÄinskas +4
Decision-makers routinely rely on expert judgments accompanied by written explanations, yet explanation quality is difficult to measure at scale. Forecasting tournaments offer a na…
cs.CL2026
When Large Language Models are More PersuasiveThan Incentivized Humans, and Why
Philipp Schoenegger, Francesco Salvi, Jiacheng Liu +39
Large Language Models (LLMs) have been shown to be highly persuasive, but when and why they outperform humans is still an open question. We compare the persuasiveness of two LLMs (…