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

arXiv: https://arxiv.org/abs/1706.09254 · HTML: https://mlsanity.com/paper/1706.09254/

## Key facts

- Cited by 253 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jun 2017.

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## Abstract (arXiv)

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. The E2E dataset poses new challenges: (1) its human reference texts show more lexical richness and syntactic variation, including discourse phenomena; (2) generating from this set requires content selection. As such, learning from this dataset promises more natural, varied and less template-like system utterances. We also establish a baseline on this dataset, which illustrates some of the difficulties associated with this data.