Sep 25, 2019 · In this paper, we propose a new encoder-decoder model based on Tensor Product Representations for Natural- to Formal-language generation, ...
Oct 5, 2019 · In this paper, we propose a new encoder-decoder model based on a structured neural representation, Tensor Product Representations (TPRs), for mapping Natural- ...
Dec 1, 2019 · In this paper, we propose a new encoder-decoder model based on Tensor Product Representations (TPRs) for Natural- to Formal-language generation, ...
Generating formal-language represented by relational tuples, such as Lisp pro- grams or mathematical operations, from natural-language input is a ...
TP-N2F considerably outperforms LSTM-based Seq2Seq models, creating a new state of the art results on two benchmarks: the MathQA dataset for math problem ...
Generating formal-language represented by relational tuples, such as Lisp programs or mathematical expressions, from a natural-language input is an ...
Bibliographic details on Natural- to formal-language generation using Tensor Product Representations.
Nov 21, 2019 · In this paper we propose a new encoder-decoder model based on. Tensor Product Representations (TPRs) for Natural- to Formal-language genera-.
Dec 13, 2019 · Contributed Talk: TP-N2F: Tensor Product Representation for Natural To Formal Language Generation. Dec 13, 2019. Speakers. KC · Kezhen Chen.
Natural- to formal-language generation using Tensor Product Representations.