Content structuring for NLG with discourse dependency trees.
-
Updated
Nov 30, 2020 - Python
Content structuring for NLG with discourse dependency trees.
The E2E Dataset, packed as a PyTorch DataSet subclass
PyTorch code for ACL 2022 paper: RoMe: A Robust Metric for Evaluating Natural Language Generation https://aclanthology.org/2022.acl-long.387/
EMNLP 2019: Generating Personalized Recipes from Historical User Preferences
T-Rex : A Large Scale Alignment of Natural Language with Knowledge Base Triples
A Constrained Text Generation Challenge Towards Generative Commonsense Reasoning
RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.
Add a description, image, and links to the nlg-dataset topic page so that developers can more easily learn about it.
To associate your repository with the nlg-dataset topic, visit your repo's landing page and select "manage topics."