Papers of Neural Topic Models (NTMs)

Check our latest topic modeling toolkit TopMost !

This repo is a collection of research papers for our survey paper A Survey on Neural Topic Models: Methods, Applications, and Challenges published at Artificial Intelligence Review.

If you are interested in our survey, please cite as

@article{wu2023survey,
title={A Survey on Neural Topic Models: Methods, Applications, and Challenges},
author={Wu, Xiaobao and Nguyen, Thong and Luu, Anh Tuan},
journal={Artificial Intelligence Review},
url={https://doi.org/10.1007/s10462-023-10661-7},
year={2024},
publisher={Springer}
}

• Papers of Neural Topic Models (NTMs)
  • Toolkits
  • NTMs with Different Structures
    • VAE-based NTM
    • NTMs with Various Priors
    • NTMs with Embeddings
    • NTMs with External Knowledge
    • NTMs with PLMs
    • NTMs with Reinforcement Learning
    • NTMs with Adversarial Training
    • NTMs with Contrastive Learning
    • NTMs with Metadata
    • NTMs with Graphs
    • Other NTMs
  • NTMs for Various Scenarios
    • Correlated NTMs
    • Short Text NTMs
    • Cross-lingual NTMs
    • Hierarchical NTMs
    • Dynamic NTMs
    • Lifelong NTMs
  • Topic Discovery by Clustering
  • Applications of NTMs
    • Text Analysis
    • Text Generation
    • Content Recommendation
  • Evaluation of Topic Models

Toolkits

1. OCTIS: Comparing and Optimizing Topic models is Simple! EACL 2021 [pdf] [code]

   Silvia Terragni, Elisabetta Fersini, Bruno Giovanni Galuzzi, Pietro Tropeano, Antonio Candelieri

2. Towards the TopMost: A Topic Modeling System Toolkit 2023 [pdf] [code]

   Xiaobao Wu, Fengjun Pan, Anh Tuan Luu

NTMs with Different Structures

VAE-based NTM

1. Neural Variational Inference for Text Processing ICML 2016 [pdf] [code]

   Yishu Miao, Lei Yu, Phil Blunsom

2. Autoencoding Variational Inference For Topic Models ICLR 2017 [pdf] [code]

   Akash Srivastava, Charles Sutton

3. Discovering Discrete Latent Topics with Neural Variational Inference ICML 2017 [pdf]

   Yishu Miao, Edward Grefenstette, Phil Blunsom

4. Coherence-aware Neural Topic Modeling EMNLP 2018 [pdf] [code]

   Ran Ding, Ramesh Nallapati, Bing Xiang

5. A Discrete Variational Recurrent Topic Model without the Reparametrization Trick NeurIPS 2020 [pdf]

   Mehdi Rezaee, Francis Ferraro

6. Topic Modeling using Variational Auto-Encoders with Gumbel-Softmax and Logistic-Normal Mixture Distributions IJCNN 2018 [pdf]

   Denys Silveira, Andr’e Carvalho, MarcoCristo, Marie-FrancineMoens

7. Improving Topic Quality by Promoting Named Entities in Topic Modeling ACL 2018 [pdf]

   Katsiaryna Krasnashchok, Salim Jouili

8. TAN-NTM: Topic Attention Networks for Neural Topic Modeling ACL 2021 [pdf]

   Madhur Panwar, Shashank Shailabh, Milan Aggarwal, Balaji Krishnamurthy

NTMs with Various Priors

1. Discovering Discrete Latent Topics with Neural Variational Inference ICML 2017 [pdf]

   Yishu Miao, Edward Grefenstette, Phil Blunsom

2. Dirichlet Variational Autoencoder arXiv 2019 [pdf]

   Weonyoung Joo, Wonsung Lee, Sungrae Park, Il-Chul Moon

3. Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model JMLR 2019 [pdf]

   Sophie Burkhardt, Stefan Kramer

4. WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling ICLR 2018 [pdf] [code]

   Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou

5. Learning VAE-LDA Models with Rounded Reparameterization Trick EMNLP 2020 [pdf]

   Runzhi Tian, Yongyi Mao, Richong Zhang

6. vONTSS: vMF based semi-supervised neural topic modeling with optimal transport EMNLP 2023 Findings [pdf] [code]

   Weijie Xu, Xiaoyu Jiang, Srinivasan Sengamedu Hanumantha Rao, Francis Iannacci, Jinjin Zhao

NTMs with Embeddings

1. Discovering Discrete Latent Topics with Neural Variational Inference ICML 2017 [pdf]

   Yishu Miao, Edward Grefenstette, Phil Blunsom

2. Topic Modeling in Embedding Spaces TACL 2020 [pdf] [code]

   Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei

3. Neural Topic Model via Optimal Transport ICLR 2021 [pdf] [code]

   He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray Buntine

4. Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021 [pdf]

   Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou

5. Representing Mixtures of Word Embeddings with Mixtures of Topic Embedding ICLR 2022 [pdf] [code]

   Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou

6. Bayesian Deep Embedding Topic Meta-Learner ICML 2022 [pdf]

   Zhibin Duan, Yishi Xu, Jianqiao Sun, Bo Chen, Wenchao Chen, Chaojie Wang, Mingyuan Zhou

7. HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding NeurIPS 2022 [pdf] [code]

   Yishi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou

8. Alleviating" Posterior Collapse''in Deep Topic Models via Policy Gradient NeurIPS 2022 [pdf]

   Yewen Li, Chaojie Wang, Zhibin Duan, Dongsheng Wang, Bo Chen, Bo An, Mingyuan Zhou

9. Effective Neural Topic Modeling with Embedding Clustering Regularization ICML 2023 [pdf] [code]

   Xiaobao Wu, Xinshuai Dong, Thong Thanh Nguyen, Anh Tuan Luu

NTMs with External Knowledge

1. Topicnet: Semantic Graph-Guided Topic Discovery NeurIPS 2021 [pdf]

   Zhibin Duan, Yishi Xu, Bo Chen, Dongsheng Wang, Chaojie Wang, Mingyuan Zhou

2. Knowledge-aware Bayesian Deep Topic Model NeurIPS 2022 [pdf]

   Dongsheng Wang, Yi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen, Mingyuan Zhou

NTMs with PLMs

1. Improving Neural Topic Models using Knowledge Distillation EMNLP 2020 [pdf] [code]

   Alexander Miserlis Hoyle, Pranav Goel, Philip Resnik

2. Cross-Lingual Contextualized Topic Models with Zero-shot Learning EACL 2021 [pdf] [code]

   Federico Bianchi, Silvia Terragni, Dirk Hovy, Debora Nozza, Elisabetta Fersini

3. Large Language Models are Implicitly Topic Models: Explaining and finding good demonstrations for in-context learning arXiv 2023 [pdf]

   Xinyi Wang, Wanrong Zhu, Michael Saxon, Mark Steyvers, William Yang Wang

NTMs with Reinforcement Learning

1. Neural Topic Model with Reinforcement Learning EMNLP 2019 [pdf]

   Lin Gui, Jia Leng, Gabriele Pergola, Yu Zhou, Ruifeng Xu, Yulan He

2. Reinforcement Learning for Topic Models arXiv 2023 [pdf]

   Jeremy Costello, Marek Z. Reformat

NTMs with Adversarial Training

1. ATM: Adversarial-neural Topic Model Information Processing & Management 2019 [pdf]

   Rui Wang, Deyu Zhou, Yulan He

2. Neural Topic Modeling with Bidirectional Adversarial Training ACL 2020 [pdf] [code]

   Rui Wang, Xuemeng Hu, Deyu Zhou, Yulan He, Yuxuan Xiong, Chenchen Ye, Haiyang Xu

3. Neural Topic Modeling with Cycle-consistent Adversarial Training EMNLP 2020 [pdf]

   Xuemeng Hu, Rui Wang, Deyu Zhou, Yuxuan Xiong

NTMs with Contrastive Learning

1. Improving Topic Disentanglement via Contrastive Learning ACM Information Processing and Management: an International Journal [pdf]

   Xixi Zhou, Jiajin Bu, Sheng Zhou, Zhi Yu, Ji Zhao, Xifeng Yan

2. Contrastive Learning for Neural Topic Model NeurIPS 2021 [pdf] [code]

   Thong Nguyen, Anh Tuan Luu

3. Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning EMNLP 2022 [pdf] [code]

   Xiaobao Wu, Anh Tuan Luu, Xinshuai Dong

4. Topic Modeling as Multi-Objective Contrastive Optimization ICLR 2024 [pdf]

   Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy Nguyen, See-Kiong Ng, Anh Tuan Luu

NTMs with Metadata

1. Neural Models for Documents with Metadata ACL 2018 [pdf] [code]

   Dallas Card, Chenhao Tan, Noah A. Smith

2. Discriminative Topic Modeling with Logistic LDA arXiv 2019 [pdf]

   Iryna Korshunova, Hanchen Xiong, Mateusz Fedoryszak, Lucas Theis

3. Layer-assisted Neural Topic Modeling over Document Networks IJCAI 2021 [pdf]

   Yiming Wang, Ximing Li, Jihong Ouyang

4. Neural Topic Model with Attention for Supervised Learning AISTATS 2020 [pdf]

   Xinyi Wang, Yi Yang

NTMs with Graphs

1. GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model EMNLP 2018 [pdf] [code]

   Qile Zhu, Zheng Feng, Xiaolin Li

2. Variational Graph Author Topic Modeling KDD 2022 [pdf]

   Delvin Ce Zhang, Hady W. Lauw

3. Topic Modeling on Document Networks with Adjacent-Encoder AAAI 2022 [pdf] [code]

   Delvin Ce Zhang, Hady W. Lauw

4. Neural Topic Modeling by Incorporating Document Relationship Graph EMNLP 2020 [pdf]

   Deyu Zhou, Xuemeng Hu, Rui Wang

5. Graph Attention Topic Modeling Network WWW 2020 [pdf]

   Liang Yang, Fan Wu, Junhua Gu, Chuan Wang, Xiaochun Cao, Di Jin, Yuanfang Guo

6. Graph Neural Topic Model with Commonsense Knowledge Information Processing & Management 2023 [pdf]

   Bingshan Zhu, Yi Cai, Haopeng Ren

7. Topic Modeling on Document Networks with Dirichlet Optimal Transport Barycenter TKDE 2023 [pdf]

   Delvin Ce Zhang, Hady W. Lauw

8. Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree KDD 2023 [pdf]

   Delvin Ce Zhang, Rex Ying, and Hady W. Lauw

9. ConvNTM: Conversational Neural Topic Model AAAI 2023 [pdf]

   Hongda Sun, Quan Tu, Jinpeng Li, Rui Yan

Other NTMs

1. A Neural Autoregressive Topic Model NeurIPS 2012 [pdf]

   Hugo Larochelle, Stanislas Lauly

2. A Novel Neural Topic Model and its Supervised Extension AAAI 2015 [pdf]

   Ziqiang Cao, Sujian Li, Yang Liu, Wenjie Li, Heng Ji

3. Document Informed Neural Autoregressive Topic Models with Distributional Prior AAAI 2019 [pdf]

   Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze

4. TextTOvec: Deep Contextualized Neural Autoregressive Topic Models of Language with Distributed Compositional Prior ICLR 2019 [pdf]

   Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze

5. Sparsemax and Relaxed Wasserstein for Topic Sparsity WSDM 2019 [pdf]

   Tianyi Lin, Zhiyue Hu, Xin Guo

6. Topic Modeling with Wasserstein Autoencoders ACL 2019 [pdf] [code]

   Feng Nan, Ran Ding, Ramesh Nallapati, Bing Xiang

7. Discovering Topics in Long-tailed Corpora with Causal Intervention ACL 2021 findings [pdf] [code]

   Xiaobao Wu, Chunping Li, Yishu Miao

NTMs for Various Scenarios

Correlated NTMs

1. Neural Variational Correlated Topic Modeling WWW 2019 [pdf]

   Luyang Liu, Heyan Huang, Yang Gao, Yongfeng Zhang, Xiaochi Wei

Short Text NTMs

1. Copula Guided Neural Topic Modelling for Short Texts SIGIR 2020 [pdf] [code]

   Lihui Lin, Hongyu Jiang, Yanghui Rao

2. Context Reinforced Neural Topic Modeling over Short Texts arXiv 2020 [pdf]

   Jiachun Feng, Zusheng Zhang, Cheng Ding, Yanghui Rao, Haoran Xie

3. Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling Decoder EMNLP 2020 [pdf] [code]

   Xiaobao Wu, Chunping Li, Yan Zhu, Yishu Miao

4. Extracting Topics with Simultaneous Word Co-occurrence and Semantic Correlation Graphs: Neural Topic Modeling for Short Texts EMNLP 2021 findings [pdf]

   Yiming Wang, Ximing Li, Xiaotang Zhou, Jihong Ouyang

5. A Neural Topic Model with Word Vectors and Entity Vectors for Short Texts Information Processing & Management 2021 [pdf]

   Xiaowei Zhao, Deqing Wang, Zhengyang Zhao, Wei Liu, Chenwei Lu, Fuzhen Zhuang

6. Meta-Complementing the Semantics of Short Texts in Neural Topic Models NeurIPS 2022 [pdf]

   Delvin Ce Zhang, Hady W. Lauw

7. Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning EMNLP 2022 [pdf] [code]

   Xiaobao Wu, Anh Tuan Luu, Xinshuai Dong

Cross-lingual NTMs

1. Learning Multilingual Topics with Neural Variational Inference NLPCC 2020 [pdf] [code]

   Xiaobao Wu, Chunping Li, Yan Zhu, Yishu Miao

2. Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling ACL 2021 [pdf]

   Aaron Mueller, Mark Dredze

3. Multilingual and Multimodal Topic Modelling with Pretrained Embeddings COLING 2022 [pdf] [code]

   Elaine Zosa, Lidia Pivovarova

4. InfoCTM: A Mutual Information Maximization Perspective of Cross-lingual Topic Modeling AAAI 2023 [pdf] [code]

   Xiaobao Wu, Xinshuai Dong, Thong Nguyen, Chaoqun Liu, Liangming Pan, Anh Tuan Luu

Hierarchical NTMs

1. Tree-structured Neural Topic Model ACL 2020 [pdf]

   Masaru Isonuma, Junichiro Mori, Danushka Bollegala, Ichiro Sakata

2. Tree-Structured Topic Modeling with Nonparametric Neural Variational Inference ACL 2021 [pdf]

   Ziye Chen, Cheng Ding, Zusheng Zhang, Yanghui Rao, Haoran Xie

3. Neural Attention-aware Hierarchical Topic Model arXiv 2021 [pdf]

   Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray Buntine

4. Neural Topic Models for Hierarchical Topic Detection and Visualization ECML PKDD 2021 [pdf]

   Dang Pham, Tuan M. V. Le

5. Hierarchical Neural Topic Modeling with Manifold Regularization World Wide Web 2021 [pdf] [code]

   Ziye Chen, Cheng Ding, Yanghui Rao, Haoran Xie, Xiaohui Tao, Gary Cheng, Fu Lee Wang

6. Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process ICML 2023 [pdf]

   Zhibin Duan, Xinyang Liu, Yudi Su, Yishi Xu, Bo Chen, Mingyuan Zhou

7. Nonlinear Structural Equation Model Guided Gaussian Mixture Hierarchical Topic Modeling ACL 2023 [pdf] [code]

   Hegang Chen, Pengbo Mao, Yuyin Lu, Yanghui Rao

8. On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling AAAI 2024 [pdf] [code]

   Xiaobao Wu, Fengjun Pan, Thong Nguyen, Yichao Feng, Chaoqun Liu, Cong-Duy Nguyen, Anh Tuan Luu

Dynamic NTMs

1. The Dynamic Embedded Topic Model arXiv 2019 [pdf] [code]

   Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei

2. Dynamic Topic Models for Temporal Document Networks ICML 2022 [pdf]

   Delvin Ce Zhang, Hady W. Lauw

3. Neural Dynamic Focused Topic Model AAAI 2023 [pdf]

   Kostadin Cvejoski, Ramsés J. Sánchez, César Ojeda

4. ANTM: An Aligned Neural Topic Model for Exploring Evolving Topics arXiv 2023 [pdf]

   Hamed Rahimi, Hubert Naacke, Camelia Constantin, Bernd Amann

Lifelong NTMs

1. Neural Topic Modeling with Continual Lifelong Learning ICML 2020 [pdf]

   Pankaj Gupta, Yatin Chaudhary, Thomas Runkler, Hinrich Schütze

2. Lifelong Topic Modeling with Knowledge-enhanced Adversarial Network WWW 2022 [pdf]

   Xuewen Zhang, Yanghui Rao, Qing Li

Topic Discovery by Clustering

Note that these studies are not real topic models since they can only produce topics while cannot infer the topic distributions of documents as required.

1. Topic Modeling with Contextualized Word Representation Clusters arXiv 2020 [pdf]

   Laure Thompson and David Mimno

2. Top2vec: Distributed Representations of Topics arXiv 2020 [pdf]

   Dimo Angelov

3. Topic Modeling with Contextualized Word Representation Clusters ACL 2020 [pdf]

   Laure Thompson, David Mimno

4. Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too EMNLP 2020 [pdf]

   Suzanna Sia, Ayush Dalmia, Sabrina J. Mielke

5. Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence ACL 2021 [pdf] [code]

   Federico Bianchi, Silvia Terragni, Dirk Hovy

6. BERTopic: Neural Topic Modeling with a Class-based TF-IDF Procedure arXiv 2022 [pdf] [code]

   Maarten Grootendorst

7. Is Neural Topic Modelling Better than Clustering? an empirical study on clustering with contextual embeddings for topics NAACL 2022 [pdf]

   Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad

8. Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts WSDM 2023 [pdf]

   Yu Zhang, Yunyi Zhang, Martin Michalski, Yucheng Jiang, Yu Meng, Jiawei Han

Applications of NTMs

Text Analysis

1. Topic Memory Networks for Short Text Classification EMNLP 2018 [pdf] [code]

   Jichuan Zeng, Jing Li, Yan Song, Cuiyun Gao, Michael R. Lyu, Irwin King

2. Neural Relational Topic Models for Scientific Article Analysis CIKM 2018 [pdf]

   Haoli Bai, Zhuangbin Chen, Michael R. Lyu, Irwin King, Zenglin Xu

3. Interaction-aware Topic Model for Microblog Conversations through Network Embedding and User Attention COLING 2018 [pdf]

   Ruifang He, Xuefei Zhang, Di Jin, Longbiao Wang, Jianwu Dang, Xiangang Li

4. TopicBERT for Energy Efficient Document Classification EMNLP 2020 Findings [pdf] [code]

   Yatin Chaudhary, Pankaj Gupta, Khushbu Saxena, Vivek Kulkarni, Thomas Runkler, Hinrich Schütze

5. Multi Task Mutual Learning for Joint Sentiment Classification and Topic Detection IEEE TKDE 2020 [pdf]

   Lin Gui; Jia Leng; Jiyun Zhou; Ruifeng Xu; Yulan He

6. Classification Aware Neural Topic Model for Covid-19 Disinformation Categorisation PLOS 2021 [pdf]

   Xingyi Song, Johann Petrak, Ye Jiang, Iknoor Singh, Diana Maynard, Kalina Bontcheva

7. Topic Modeling on Podcast Short-text Metadata ECIR 2022 [pdf]

   Francisco B. Valero, Marion Baranes, Elena V. Epure

8. Topic Modeling Techniques for Text Mining over a Large-Scale Scientific and Biomedical Text Corpus IJACI 2022 [pdf]

   Sandhya Avasthi, Ritu Chauhan, Debi Prasanna Acharjya

9. Topic Modeling for Multi-Aspect Listwise Comparisons CIKM 2021 [pdf] [code]

   Delvin Ce Zhang, Hady W. Lauw

Text Generation

1. A Topic Augmented Text Generation Model: Joint Learning of Semantics and Structural Features EMNLP 2019 [pdf]

   Hongyin Tang, Miao Li, Beihong Jin

2. Topic-Guided Abstractive Text Summarization: a Joint Learning Approach arXiv 2020 [pdf]

   Chujie Zheng, Kunpeng Zhang, Harry Jiannan Wang, Ling Fan, Zhe Wang

3. What You Say and How You Say it: Joint Modeling of Topics and Discourse in Microblog Conversations TACL 2019 [pdf]

   Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King

4. Enriching and Controlling Global Semantics for Text Summarization EMNLP 2021 [pdf]

   Thong Nguyen, Anh Tuan Luu, Truc Lu, Tho Quan

5. Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks COLING 2020 [pdf]

   Peng Cui, Le Hu, Yuanchao Liu

6. Recurrent Hierarchical Topic-guided RNN for Language Generation ICML 2020 [pdf]

   Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou

7. TopNet: Learning from Neural Topic Model to Generate Long Stories KDD 2021 [pdf]

   Yazheng Yang, Boyuan Pan, Deng Cai, Huan Sun

8. HTKG: Deep Keyphrase Generation with Neural Hierarchical Topic Guidance SIGIR 2022 [pdf]

   Yuxiang Zhang, Tao Jiang, Tianyu Yang, Xiaoli Li, Suge Wang

9. TopicRNN: A Recurrent Neural Network with Long-range Semantic Dependency ICLR 2017 [pdf] [code]

   Adji B. Dieng, Chong Wang, Jianfeng Gao, John Paisley

10. DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM EMNLP 2023 Finding [pdf] [code]

    Weijie Xu, Wenxiang Hu, Fanyou Wu, Srinivasan H. Sengamedu

Content Recommendation

1. Structured Neural Topic Models for Reviews AISTATS 2019 [pdf]

   Babak Esmaeili, Hongyi Huang, Byron C. Wallace, Jan-Willem van de Meent

2. Graph Neural Collaborative Topic Model for Citation Recommendation ACM TOIS 2021 [pdf]

   Qianqian Xie, Yutao Zhu, Jimin Huang, Pan Du, Jian-Yun Nie

Evaluation of Topic Models

1. Evaluation Methods for Topic Models ICML 2009 [pdf]

   Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David Mimno

2. Reading Tea Leaves: How Humans Interpret Topic Models NeurIPS 2009 [pdf]

   Jonathan Chang, Sean Gerrish, Chong Wang, Jordan Boyd-graber, David Blei

3. Estimating Likelihoods for Topic Models ACML 2009 [pdf]

   Wray Buntine

4. Automatic Evaluation of Topic Coherence NAACL 2010 [pdf]

   David Newman, Jey Han Lau, Karl Grieser, Timothy Baldwin

5. Topic Model or Topic Twaddle? Re-evaluating Semantic Interpretability Measures NAACL 2021 [pdf]

   Caitlin Doogan, Wray Buntine

6. Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality ACL 2014 [pdf] [code]

   Jey Han Lau, David Newman, Timothy Baldwin

7. Exploring the Space of Topic Coherence Measures WSDM 2015 [pdf] [code]

   Michael Röder, Andreas Both, Alexander Hinneburg

8. Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence NeurIPS 2021 [pdf]

   Alexander Hoyle, Pranav Goel, Denis Peskov, Andrew Hian-Cheong, Jordan Boyd-Graber, Philip Resnik

9. Are Neural Topic Models Broken? EMNLP 2022 [pdf]

   Alexander Hoyle, Pranav Goel, Rupak Sarkar, Philip Resnik

10. Benchmarking Neural Topic Models: An Empirical Study ACL 2021 [pdf]

    Thanh-Nam Doan, Tuan-Anh Hoang

11. Re-visiting Automated Topic Model Evaluation with Large Language Models arXiv 2023 [pdf]

    Dominik Stammbach, Vilém Zouhar, Alexander Hoyle, Mrinmaya Sachan, Elliott Ash

12. Revisiting Automated Topic Model Evaluation with Large Language Models EMNLP 2023 [pdf]

    Dominik Stammbach, Vilém Zouhar, Alexander Hoyle, Mrinmaya Sachan, Elliott Ash