We develop a framework for partial identification of causal effects under violations of key assumptions when combining heterogeneous data sources.

A dataset and an algorithm for multi-modal object tracking.

We propose a novel influence-based adaptive sample borrowing approach to enhance treatment effect estimation in RCTs by effectively incorporating external controls.