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Neural networks with tree-based sentence encoders have shown better results on many downstream tasks. Most of existing tree-based encoders adopt syntactic parsing trees as the explicit structure prior. To study the effectiveness of different tree structures, we replace the parsing trees with trivial trees (i.e., binary balanced tree, left-branching tree and right-branching tree) in the encoders. Though trivial trees contain no syntactic information, those encoders get competitive or even betterdoi:10.18653/v1/d18-1492 dblp:conf/emnlp/ShiZCL18 fatcat:a2hiqrn7szce7d4azhwu3egkyy