Papers with Detecting events

2 papers
Event Detection with Neural Networks: A Rigorous Empirical Evaluation (D18-1)

Copied to clipboard

Challenge: Neural network models have been the most successful for event detection, but they ignore syntactic relationships in the text.
Approach: They propose a GRU-based model that combines syntactic information along with temporal structure through an attention mechanism.
Outcome: The proposed model is competitive with existing models on a ACE2005 dataset.
Extracting Event Temporal Relations via Hyperbolic Geometry (2021.emnlp-main)

Copied to clipboard

Challenge: Recent neural approaches to event temporal relation extraction map events to embeddings in the Euclidean space and train a classifier to detect temporal relations between event pairs.
Approach: They propose to embed events into hyperbolic spaces to model hierarchical structures . they propose to use hyperbolical embeddings to directly infer event relations .
Outcome: The proposed architecture is based on two approaches to encode events and their temporal relations in hyperbolic spaces.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations