Summary generation based on comparison objects can include receiving text descriptions of a target object and at least one comparison object. Semantic vectors from the text descriptions can be obtained, using a deep learning based semantic extraction model. The semantic vectors can be input to a generator model trained using an adversarial machine learning technique, the generator model outputting a text summary of the target object describing only unique characteristics of the target object different from characteristics of the at least one comparison object and excluding the characteristics of the at least one comparison object.