Knowledge-Enhanced NLG

The slides are from this repo. The presenter was Wenhao Yu.

Reference

@inproceedings{10.1145/3539597.3572720,
author = {Zhu, Chenguang and Xu, Yichong and Ren, Xiang and Lin, Bill Yuchen and Jiang, Meng and Yu, Wenhao},
title = {Knowledge-Augmented Methods for Natural Language Processing},
year = {2023},
isbn = {9781450394079},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3539597.3572720},
doi = {10.1145/3539597.3572720},
abstract = {Knowledge in NLP has been a rising trend especially after the advent of large-scale pre-trained models. Knowledge is critical to equip statistics-based models with common sense, logic and other external information. In this tutorial, we will introduce recent state-of-the-art works in applying knowledge in language understanding, language generation and commonsense reasoning.},
booktitle = {Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining},
pages = {1228–1231},
numpages = {4},
keywords = {language generation, knowledge-augmented methods, natural language understanding, commonsense reasoning},
location = {Singapore, Singapore},
series = {WSDM '23}
}