ACL 2023long5 citations
SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres
Shumin Deng, Shengyu Mao, Ningyu Zhang, Bryan Hooi
Abstract
Event-centric structured prediction involves predicting structured outputs of events. In most NLP cases, event structures are complex with manifold dependency, and it is challenging to effectively represent these complicated structured events. To address these issues, we propose Structured Prediction with Energy-based Event-Centric Hyperspheres (SPEECH). SPEECH models complex dependency among event structured components with energy-based modeling, and represents event classes with simple but effective hyperspheres. Experiments on two unified-annotated event datasets indicate that SPEECH is predominant in event detection and event-relation extraction tasks.
BibTeX
@inproceedings{deng-etal-2023-speech,
title = "{SPEECH}: Structured Prediction with Energy-Based Event-Centric Hyperspheres",
author = "Deng, Shumin and
Mao, Shengyu and
Zhang, Ningyu and
Hooi, Bryan",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.21/",
doi = "10.18653/v1/2023.acl-long.21",
pages = "351--363"
}