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In the analogy, four-momenta are like words and the\nclustering history of sequential recombination jet algorithms is like the\nparsing of a sentence. Our approach works directly with the four-momenta of a\nvariable-length set of particles, and the jet-based tree structure varies on an\nevent-by-event basis. Our experiments highlight the flexibility of our method\nfor building task-specific jet embeddings and show that recursive architectures\nare significantly more accurate and data efficient than previous image-based\nnetworks. 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