Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning

arXiv:2605.11889v1 Announce Type: cross Abstract: Collaborative machine learning involves training high-quality models using datasets from a number of sources. To incentivize sources to share data, existing data valuation methods fairly reward each source based on its data submitted as is. However, as these methods do not verify nor incentivize data truthfulness, the sources can manipulate their data (e.g., by submitting duplicated or noisy data) to artificially increase their valuations and rew