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This paper introduces Monotone Alternating Splines (MAS), a novel framework for modeling cumulative conditional intensity functions in temporal point processes. MAS overcomes structural limitations of existing monotone neural networks, achieving better accuracy and efficiency on synthetic and real datasets.