As the scale of machine learning models increases, trends such as scaling laws anticipate
consistent downstream improvements in predictive accuracy. However, these trends take the …

Emerging marketplaces for large language models and other large-scale machine learning
(ML) models appear to exhibit market concentration, which has raised concerns about …

This paper analyzes cooperative data-sharing between competitors vying to predict a
consumer's tastes. We design optimal data-sharing schemes both for when they compete …

Two firms are engaged in a competitive prediction task. Each firm has two sources of data—
labeled historical data and unlabeled inference-time data—and uses the former to derive a …

We present a model of seller expertise, expressed in our setting as the accuracy of seller
beliefs about buyers. Both buyers and sellers are heterogeneous ex-ante, the former with …

Technological innovations have allowed some sellers to collect detailed information about
buyers. I study these changes in a standard search-theoretic model of imperfect competition …

Two firms are engaged in a competitive prediction task. Each firm has two sources of data-
labeled historical data and unla-beled inference-time data—and uses the former to derive a …

This paper studies cooperative data-sharing between competitors vying to predict a
consumer's tastes. We design optimal datasharing schemes both for when they compete …