Link Sharing Practice

Link sharing practices, encompassing the exchange of data, models, or predictions, are a central focus in various scientific domains, aiming to improve collaboration, reproducibility, and efficiency. Current research investigates optimal strategies for sharing information in competitive settings, mitigating vulnerabilities in distributed learning (like federated learning) through techniques such as partial sharing, and analyzing the impact of sharing on outcomes like wealth inequality or scientific recognition. These studies utilize diverse approaches, including Bayesian frameworks, curriculum learning for neural architecture search, and simulations of artificial societies, to understand the benefits and drawbacks of different sharing mechanisms. The findings contribute to a better understanding of collaborative processes and inform the design of more robust and efficient systems across diverse fields.