We present the T emporal Graph Benchmark (TGB), a collection of challenging and diverse benchmark datasets for realistic, reproducible, and robust evaluation of machine learning models on temporal graphs.

A fundamental difference between our learning problem from standard RL problems is that the realized reward feedback from conversion incrementality ismixed and delayed.