In this work, we adopt an approach that is inspired by (Lu et al., 2008;Lu, 2014), which learns a latent joint representation for words and semantics in the form of hybrid trees where word-semantics correspondence information is captured.
we introduce a text-math tree representation that jointly encodes both text and the math expression tree.