Data to 7 Oct 2026

Discovering Discrete Latent Topics with Neural Variational Inference

arXiv 1706.00359 ↗First posted 1 Jun 2017cs.CL cs.AI cs.IRcited by 79

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Abstract (arXiv)

Topic models have been widely explored as probabilistic generative models of documents. Traditional inference methods have sought closed-form derivations for updating the models, however as the expressiveness of these models grows, so does the difficulty of performing fast and accurate inference over their parameters. This paper presents alternative neural approaches to topic modelling by providing parameterisable distributions over topics which permit training by backpropagation in the framework of neural variational inference. In addition, with the help of a stick-breaking construction, we propose a recurrent network that is able to discover a notionally unbounded number of topics, analogous to Bayesian non-parametric topic models. Experimental results on the MXM Song Lyrics, 20NewsGroups and Reuters News datasets demonstrate the effectiveness and efficiency of these neural topic models.

Key facts. Cited by 79 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Jun 2017.

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Citing papers per year: 2021: 22; 2022: 10; 2023: 19; 2024: 9; 2025: 11; 2026: 8.

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2023Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learningcited by 149
2021Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherencecited by 74
2023Guiding Language Model Reasoning with Planning Tokenscited by 58
2021Topic Modelling Meets Deep Neural Networks: A Surveycited by 51
2021Contrastive Learning for Neural Topic Modelcited by 48
2023Effective Neural Topic Modeling with Embedding Clustering Regularizationcited by 46
2022Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learningcited by 38
2024FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Modelcited by 34
2021Sequence-to-Sequence Learning with Latent Neural Grammarscited by 30
2021Enriching and Controlling Global Semantics for Text Summarizationcited by 20
2021Topic-Guided Abstractive Multi-Document Summarizationcited by 19
2024On the Affinity, Rationality, and Diversity of Hierarchical Topic Modelingcited by 18

38 more

2024A Survey on Neural Topic Models: Methods, Applications, and Challengescited by 18
2021Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modelingcited by 16
2023vONTSS: vMF based semi-supervised neural topic modeling with optimal transportcited by 16
2023DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLMcited by 16
2024Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusioncited by 16
2021Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidancecited by 14
2021ePiC: Employing Proverbs in Context as a Benchmark for Abstract Language Understandingcited by 14
2022Neural Topic Modeling of Psychotherapy Sessionscited by 13
2023VIBE: Topic-Driven Temporal Adaptation for Twitter Classificationcited by 12
2024LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Modelscited by 11
2024Neural Topic Modeling with Large Language Models in the Loopcited by 10
2021Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modelingcited by 8
2021Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversationscited by 8
2022SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learningcited by 8
2023Neural Dynamic Focused Topic Modelcited by 8
2024COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modelingcited by 8
2022Knowledge Management System with NLP-Assisted Annotations: A Brief Survey and Outlookcited by 7
2021Out-of-Town Recommendation with Travel Intention Modelingcited by 6
2021Neural Attention-Aware Hierarchical Topic Modelcited by 6
2023A Topic-aware Summarization Framework with Different Modal Side Informationcited by 6
2023Towards Open-World Product Attribute Mining: A Lightly-Supervised Approachcited by 6
2023Diversity-Aware Coherence Loss for Improving Neural Topic Modelscited by 5
2021Bayesian Topic Regression for Causal Inferencecited by 4
2025Bridging the Evaluation Gap: Leveraging Large Language Models for Topic Model Evaluationcited by 4
2021Topic Driven Adaptive Network for Cross-Domain Sentiment Classificationcited by 3
2022Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches and Future Directionscited by 3
2023Topics as Entity Clusters: Entity-based Topics from Large Language Models and Graph Neural Networkscited by 3
2023TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Artscited by 3
2023KDSTM: Neural Semi-supervised Topic Modeling with Knowledge Distillationcited by 3
2025Sparse Autoencoders are Topic Modelscited by 3
2021TopNet: Learning from Neural Topic Model to Generate Long Storiescited by 2
2022Knowledge-aware Document Summarization: A Survey of Knowledge, Embedding Methods and Architecturescited by 2
2022Time Will Change Things: An Empirical Study on Dynamic Language Understanding in Social Media Classificationcited by 2
2025Importance-aware Topic Modeling for Discovering Public Transit Risk from Noisy Social Mediacited by 2
2021Who Responded to Whom: The Joint Effects of Latent Topics and Discourse in Conversation Structurecited by 1
2022Neural Topic Modeling with Deep Mutual Information Estimationcited by 1
2022Towards Better Understanding with Uniformity and Explicit Regularization of Embeddings in Embedding-based Neural Topic Modelscited by 1
2023Reinforcement Learning for Topic Modelscited by 1

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