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20202025
most citedR2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling

11 citations · 16 across the 11 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

cs.CL2023

Augmenting Transformers with Recursively Composed Multi-grained Representations

Xiang Hu, Qingyang Zhu, Kewei Tu +1

We present ReCAT, a recursive composition augmented Transformer that is able to explicitly model hierarchical syntactic structures of raw texts without relying on gold trees during…

cs.CL2023★ 2 cited

A Multi-Grained Self-Interpretable Symbolic-Neural Model For Single/Multi-Labeled Text Classification

Xiang Hu, Xinyu Kong, Kewei Tu

Deep neural networks based on layer-stacking architectures have historically suffered from poor inherent interpretability. Meanwhile, symbolic probabilistic models function with cl…