mlsanityData to 14 Oct 2026

Towards the TopMost: A Topic Modeling System Toolkit

arXiv 2309.06908 ↗First posted 13 Sep 2023cs.CL cs.AI cs.IRcited by 21

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Abstract (arXiv)

Topic models have a rich history with various applications and have recently been reinvigorated by neural topic modeling. However, these numerous topic models adopt totally distinct datasets, implementations, and evaluations. This impedes quick utilization and fair comparisons, and thereby hinders their research progress and applications. To tackle this challenge, we in this paper propose a Topic Modeling System Toolkit (TopMost). Compared to existing toolkits, TopMost stands out by supporting more extensive features. It covers a broader spectrum of topic modeling scenarios with their complete lifecycles, including datasets, preprocessing, models, training, and evaluations. Thanks to its highly cohesive and decoupled modular design, TopMost enables rapid utilization, fair comparisons, and flexible extensions of diverse cutting-edge topic models. Our code, tutorials, and documentation are available at https://github.com/bobxwu/topmost.

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 24 of its 71 references that are in the map. First posted on arXiv 13 Sep 2023.

Builds on

24 of 71 references.

References · 24

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 2016Pointer Sentinel Mixture Modelscited by 3,096
  3. 2016Variational Inference: A Review for Statisticianscited by 1,472
  4. 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 801
  5. 2019Topic Modeling in Embedding Spacescited by 224
  6. 2017Autoencoding Variational Inference For Topic Modelscited by 169
  7. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  8. 2020Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherencecited by 121
  9. 2021Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherencecited by 74
  10. 2019Topic Modeling with Wasserstein Autoencoderscited by 53
  11. 2021Topic Modelling Meets Deep Neural Networks: A Surveycited by 51
  12. 2020Neural Topic Model via Optimal Transportcited by 50
12 more
  1. 2021Contrastive Learning for Neural Topic Modelcited by 48
  2. 2017Neural Models for Documents with Metadatacited by 46
  3. 2023Effective Neural Topic Modeling with Embedding Clustering Regularizationcited by 46
  4. 2019The Dynamic Embedded Topic Modelcited by 41
  5. 2019Short Text Topic Modeling Techniques, Applications, and Performance: A Surveycited by 38
  6. 2022Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learningcited by 38
  7. 2023InfoCTM: A Mutual Information Maximization Perspective of Cross-Lingual Topic Modelingcited by 24
  8. 2021Sawtooth Factorial Topic Embeddings Guided Gamma Belief Networkcited by 23
  9. 2022HyperMiner: Topic Taxonomy Mining with Hyperbolic Embeddingcited by 15
  10. 2017Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean?cited by 10
  11. 2018Learning Multilingual Topics from Incomparable Corpuscited by 5
  12. 2018STTM: A Tool for Short Text Topic Modelingcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 11; 2025: 6; 2026: 4.

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  1. 2024AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledgecited by 44
  2. 2024AKEW: Assessing Knowledge Editing in the Wildcited by 36
  3. 2024A Survey of Recent Backdoor Attacks and Defenses in Large Language Modelscited by 36
  4. 2024FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Modelcited by 35
  5. 2024Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillationcited by 27
  6. 2024A Survey on Neural Topic Models: Methods, Applications, and Challengescited by 18
  7. 2024Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusioncited by 16
  8. 2024Topic Modeling as Multi-Objective Contrastive Optimizationcited by 12
  9. 2024Are LLMs Good Zero-Shot Fallacy Classifiers?cited by 12
  10. 2024NeuroMax: Enhancing Neural Topic Modeling via Maximizing Mutual Information and Group Topic Regularizationcited by 9
  11. 2025Read as You See: Guiding Unimodal LLMs for Low-Resource Explainable Harmful Meme Detectioncited by 7
  12. 2024GloCOM: A Short Text Neural Topic Model via Global Clustering Contextcited by 4
9 more
  1. 2025Enhancing Multimodal Entity Linking with Jaccard Distance-based Conditional Contrastive Learning and Contextual Visual Augmentationcited by 3
  2. 2025Sparse Autoencoders are Topic Modelscited by 3
  3. 2025E-LDA: Toward Interpretable LDA Topic Models with Strong Guarantees in Logarithmic Parallel Timecited by 1
  4. 2025Hierarchical Graph Topic Modeling with Topic Tree-based Transformercited by 0
  5. 2025LLM as Attention-Informed NTM and Topic Modeling as long-input Generation: Interpretability and long-Context Capabilitycited by 0
  6. 2026Improving Topic Modeling by Distilling Soft Labels from Language Modelscited by 0
  7. 2026Disentangling Similarity and Relatedness in Topic Modelscited by 0
  8. 2026Domain-Agnostic Neural Topic Modeling with Contextual Token-Level Semantic Graph Representationcited by 0
  9. 2026A Manifold-Aware Topic Modeling Approach via Rank-Based Prototypescited by 0