DeepAI AI Chat
Log In Sign Up

Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization

by   Hai Ye, et al.
Northeastern University
University of Southern California
The Hong Kong Polytechnic University

Semantic parsing aims to transform natural language (NL) utterances into formal meaning representations (MRs), whereas an NL generator achieves the reverse: producing a NL description for some given MRs. Despite this intrinsic connection, the two tasks are often studied separately in prior work. In this paper, we model the duality of these two tasks via a joint learning framework, and demonstrate its effectiveness of boosting the performance on both tasks. Concretely, we propose a novel method of dual information maximization (DIM) to regularize the learning process, where DIM empirically maximizes the variational lower bounds of expected joint distributions of NL and MRs. We further extend DIM to a semi-supervision setup (SemiDIM), which leverages unlabeled data of both tasks. Experiments on three datasets of dialogue management and code generation (and summarization) show that performance on both semantic parsing and NL generation can be consistently improved by DIM, in both supervised and semi-supervised setups.


page 1

page 2

page 3

page 4


Towards Unsupervised Language Understanding and Generation by Joint Dual Learning

In modular dialogue systems, natural language understanding (NLU) and na...

StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing

Semantic parsing is the task of transducing natural language (NL) uttera...

Dual Inference for Improving Language Understanding and Generation

Natural language understanding (NLU) and Natural language generation (NL...

Dual Learning for Semi-Supervised Natural Language Understanding

Natural language understanding (NLU) converts sentences into structured ...

A Generative Model for Joint Natural Language Understanding and Generation

Natural language understanding (NLU) and natural language generation (NL...

Code Generation as a Dual Task of Code Summarization

Code summarization (CS) and code generation (CG) are two crucial tasks i...

On Semi-Supervised Multiple Representation Behavior Learning

We propose a novel paradigm of semi-supervised learning (SSL)–the semi-s...