4 papers
Randomness in large language models: What researchers need to know (and report)
Guillaume Coqueret, Joan Llull, Florian Oswald +3
Large language models (LLMs) are increasingly used to generate data for research. Typical use cases are classifications, annotations, information extraction, and generation of nume…
Global p-Values in Multi-Design Studies
Guillaume Coqueret, Yuming Zhang, Christophe Pérignon +2
Replicability issues -- referring to the difficulty or failure of independent researchers to corroborate the results of published studies -- have hindered the meaningful progressio…
Overparametrized models with posterior drift
Guillaume Coqueret, Martial Laguerre
This paper investigates the impact of posterior drift on out-of-sample forecasting accuracy in overparametrized machine learning models. We document the loss in performance when th…
Forking paths in financial economics
Guillaume Coqueret
We argue that spanning large numbers of degrees of freedom in empirical analysis allows better characterizations of effects and thus improves the trustworthiness of conclusions. Ou…