Semantically-informed Hierarchical Event Modeling

Implementation of "SHEM-Semantically-informed Hierarchical Event Modeling"

This work presents a new event modeling framework that combines sequential latent variables with ontological knowledge, achieving superior performance by up to 8.5% on various datasets and evaluation metrics compared to previous state-of-the-art methods.

Skills: Natural Language Processing (NLP) 路 Large Language Models (LLM) 路 Machine Learning 路 PyTorch 路 Scikit-Learn 路 Generative AI 路 Python 路 NLTK 路 spaCy 路 Data Engineering 路 Data Analysis 路 Matplotlib

Published in: *SEM, ACL 2023 Paper Link: GitHub Link:

SHEM flowchart