A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021.
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Updated
Jan 16, 2024 - Python
A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021.
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
A Topic Modeling System Toolkit
Code for Effective Neural Topic Modeling with Embedding Clustering Regularization (ICML2023)
Papers of Neural Topic Models (NTMs)
Aligned Neural Topic Model (ANTM) for Exploring Evolving Topics: a dynamic neural topic model that uses document embeddings (data2vec) to compute clusters of semantically similar documents at different periods, and aligns document clusters to represent topic evolution.
"Modeling electronic health record data using an end-to-end knowledge-graph-informed topic model" paper on Sci Rep (2022)
Code for On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling (AAAI 2024)
This repository is associated with the paper "Do Neural Topic Models Really Need Dropout? Analysis of the Effect of Dropout in Topic Modeling", accepted at EACL 2023.
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