We present ToTTo, an open-domain English table-to-text dataset with over 120,000 training
examples that proposes a controlled generation task: given a Wikipedia table and a set of …

Neural encoder-decoder models for language generation can be trained to predict words
directly from linguistic or non-linguistic inputs. When generating with these so-called end-to …

We present DART, an open domain structured DAta Record to Text generation dataset with
over 82k instances (DARTs). Data-to-Text annotations can be a costly process, especially …

This paper provides a comprehensive analysis of the first shared task on End-to-End Natural
Language Generation (NLG) and identifies avenues for future research based on the results …

Traditionally, most data-to-text applications have been designed using a modular pipeline
architecture, in which non-linguistic input data is converted into natural language through …

Data-to-text Generation (D2T) aims to generate textual natural language statements that can
fluently and precisely describe the structured data such as graphs, tables, and meaning …

Recent developments in neural networks have led to the advance in data-to-text generation.
However, the lack of ability of neural models to control the structure of generated output can …

Abstract Data-to-Text Generation (DTG) is a subfield of Natural Language Generation
aiming at transcribing structured data in natural language descriptions. The field has been …

Tables are often created with hierarchies, but existing works on table reasoning mainly focus
on flat tables and neglect hierarchical tables. Hierarchical tables challenge existing methods …

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. Recent end-to …