Two Birds, One Stone: A Simple, Unified Model for Text Generation from Structured and Unstructured Data

Hamidreza Shahidi, Ming Li, Jimmy Lin


Abstract
A number of researchers have recently questioned the necessity of increasingly complex neural network (NN) architectures. In particular, several recent papers have shown that simpler, properly tuned models are at least competitive across several NLP tasks. In this work, we show that this is also the case for text generation from structured and unstructured data. We consider neural table-to-text generation and neural question generation (NQG) tasks for text generation from structured and unstructured data, respectively. Table-to-text generation aims to generate a description based on a given table, and NQG is the task of generating a question from a given passage where the generated question can be answered by a certain sub-span of the passage using NN models. Experimental results demonstrate that a basic attention-based seq2seq model trained with the exponential moving average technique achieves the state of the art in both tasks. Code is available at https://github.com/h-shahidi/2birds-gen.
Anthology ID:
2020.acl-main.355
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Editors:
Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3864–3870
Language:
URL:
https://aclanthology.org/2020.acl-main.355
DOI:
10.18653/v1/2020.acl-main.355
Bibkey:
Cite (ACL):
Hamidreza Shahidi, Ming Li, and Jimmy Lin. 2020. Two Birds, One Stone: A Simple, Unified Model for Text Generation from Structured and Unstructured Data. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 3864–3870, Online. Association for Computational Linguistics.
Cite (Informal):
Two Birds, One Stone: A Simple, Unified Model for Text Generation from Structured and Unstructured Data (Shahidi et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.355.pdf
Video:
 http://slideslive.com/38929197
Code
 h-shahidi/2birds-gen
Data
SQuAD