no code implementations • 3 May 2024 • Wanlong Liu, Li Zhou, Dingyi Zeng, Yichen Xiao, Shaohuan Cheng, Chen Zhang, Grandee Lee, Malu Zhang, Wenyu Chen
Recent mainstream event argument extraction methods process each event in isolation, resulting in inefficient inference and ignoring the correlations among multiple events.
no code implementations • 8 Oct 2023 • Wanlong Liu, Dingyi Zeng, Li Zhou, Yichen Xiao, Weishan Kong, Malu Zhang, Shaohuan Cheng, Hongyang Zhao, Wenyu Chen
Document-level event argument extraction is a crucial yet challenging task within the field of information extraction.
1 code implementation • Association for Computational Linguistics 2023 • Wanlong Liu, Shaohuan Cheng, Dingyi Zeng, Hong Qu
Document-level event argument extraction poses new challenges of long input and cross-sentence inference compared to its sentence-level counterpart.
Ranked #1 on Event Argument Extraction on WikiEvents (F1 metric)
no code implementations • 15 Oct 2021 • Li Zhou, Wenyu Chen, Dingyi Zeng, Shaohuan Cheng, Wanlong Liu, Malu Zhang, Hong Qu
To address these drawbacks, we present a novel message-passing paradigm, based on the properties of multi-step message source, node-specific message output, and multi-space message interaction.