Data-to-Text Generation

32 papers with code · Natural Language Processing
Subtask of Text Generation

Data-to-text generation is the task of generating text from a data source.

( Image credit: Data-to-Text Generation with Content Selection and Planning )

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Greatest papers with code

Few-Shot Natural Language Generation by Rewriting Templates

30 Apr 2020google-research-datasets/dstc8-schema-guided-dialogue

In this work, we propose a template rewriting method for Natural Language Generation (NLG), where the number of templates scales only linearly with the number of slots.

DATA-TO-TEXT GENERATION LANGUAGE MODELLING

Findings of the E2E NLG Challenge

WS 2018 UFAL-DSG/tgen

This paper summarises the experimental setup and results of the first shared task on end-to-end (E2E) natural language generation (NLG) in spoken dialogue systems.

DATA-TO-TEXT GENERATION SPOKEN DIALOGUE SYSTEMS

The E2E Dataset: New Challenges For End-to-End Generation

WS 2017 UFAL-DSG/tgen

This paper describes the E2E data, a new dataset for training end-to-end, data-driven natural language generation systems in the restaurant domain, which is ten times bigger than existing, frequently used datasets in this area.

DATA-TO-TEXT GENERATION

Challenges in Data-to-Document Generation

EMNLP 2017 harvardnlp/data2text

Recent neural models have shown significant progress on the problem of generating short descriptive texts conditioned on a small number of database records.

DATA-TO-TEXT GENERATION

Deep Graph Convolutional Encoders for Structured Data to Text Generation

WS 2018 diegma/graph-2-text

Most previous work on neural text generation from graph-structured data relies on standard sequence-to-sequence methods.

DATA-TO-TEXT GENERATION GRAPH-TO-SEQUENCE

Improving Quality and Efficiency in Plan-based Neural Data-to-Text Generation

WS 2019 AmitMY/chimera

We follow the step-by-step approach to neural data-to-text generation we proposed in Moryossef et al (2019), in which the generation process is divided into a text-planning stage followed by a plan-realization stage.

DATA-TO-TEXT GENERATION

Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation

NAACL 2019 AmitMY/chimera

We propose to split the generation process into a symbolic text-planning stage that is faithful to the input, followed by a neural generation stage that focuses only on realization.

DATA-TO-TEXT GENERATION GRAPH-TO-SEQUENCE

Data-to-Text Generation with Content Selection and Planning

3 Sep 2018ratishsp/data2text-plan-py

Recent advances in data-to-text generation have led to the use of large-scale datasets and neural network models which are trained end-to-end, without explicitly modeling what to say and in what order.

DATA-TO-TEXT GENERATION