mlsanityData to 7 Oct 2026

Topic-Guided Variational Autoencoders for Text Generation

arXiv 1903.07137 ↗First posted 17 Mar 2019cs.CLcited by 44

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Abstract (arXiv)

We propose a topic-guided variational autoencoder (TGVAE) model for text generation. Distinct from existing variational autoencoder (VAE) based approaches, which assume a simple Gaussian prior for the latent code, our model specifies the prior as a Gaussian mixture model (GMM) parametrized by a neural topic module. Each mixture component corresponds to a latent topic, which provides guidance to generate sentences under the topic. The neural topic module and the VAE-based neural sequence module in our model are learned jointly. In particular, a sequence of invertible Householder transformations is applied to endow the approximate posterior of the latent code with high flexibility during model inference. Experimental results show that our TGVAE outperforms alternative approaches on both unconditional and conditional text generation, which can generate semantically-meaningful sentences with various topics.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Mar 2019.

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Citing papers per year: 2020: 1; 2021: 13; 2022: 9; 2023: 11; 2024: 6; 2025: 3; 2026: 1.

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  1. 2022A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Modelscited by 128
  2. 2022Latent Diffusion Energy-Based Model for Interpretable Text Modelingcited by 67
  3. 2021Topic Modelling Meets Deep Neural Networks: A Surveycited by 51
  4. 2023Controllable Mixed-Initiative Dialogue Generation through Promptingcited by 32
  5. 2023BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inferencecited by 30
  6. 2021Attribute Alignment: Controlling Text Generation from Pre-trained Language Modelscited by 27
  7. 2021Math Word Problem Generation with Mathematical Consistency and Problem Context Constraintscited by 27
  8. 2023Mixture of Soft Prompts for Controllable Data Generationcited by 23
  9. 2022Why is constrained neural language generation particularly challenging?cited by 19
  10. 2021Variational Topic Inference for Chest X-Ray Report Generationcited by 16
  11. 2023DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLMcited by 16
  12. 2024LLM-based multi-agent poetry generation in non-cooperative environmentscited by 15
32 more
  1. 2021Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidancecited by 14
  2. 2021Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classificationcited by 14
  3. 2021Controllable and Diverse Text Generation in E-commercecited by 13
  4. 2024Learning to Plan for Language Modeling from Unlabeled Datacited by 12
  5. 2022Are Neural Topic Models Broken?cited by 11
  6. 2021Constrained Text Generation with Global Guidance -- Case Study on CommonGencited by 10
  7. 2022AdaVAE: Exploring Adaptive GPT-2s in Variational Auto-Encoders for Language Modelingcited by 10
  8. 2023Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generationcited by 9
  9. 2021Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priorscited by 8
  10. 2024Sentiment-oriented Transformer-based Variational Autoencoder Network for Live Video Commentingcited by 7
  11. 2022Plug-and-Play Recipe Generation with Content Planningcited by 5
  12. 2023Advancing Precise Outline-Conditioned Text Generation with Task Duality and Explicit Outline Controlcited by 5
  13. 2023Diversity-Aware Coherence Loss for Improving Neural Topic Modelscited by 5
  14. 2021EXoN: EXplainable encoder Networkcited by 4
  15. 2021Learning Graphon Autoencoders for Generative Graph Modelingcited by 4
  16. 2021CCGG: A Deep Autoregressive Model for Class-Conditional Graph Generationcited by 4
  17. 2022PCAE: A Framework of Plug-in Conditional Auto-Encoder for Controllable Text Generationcited by 4
  18. 2020Nested-Wasserstein Self-Imitation Learning for Sequence Generationcited by 3
  19. 2022RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generatorscited by 3
  20. 2023Revisiting Topic-Guided Language Modelscited by 3
  21. 2026Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Reviewcited by 3
  22. 2021TopNet: Learning from Neural Topic Model to Generate Long Storiescited by 2
  23. 2022An Overview on Controllable Text Generation via Variational Auto-Encoderscited by 1
  24. 2023Semantic Similarity Measure of Natural Language Text through Machine Learning and a Keyword-Aware Cross-Encoder-Ranking Summarizer -- A Case Study Using UCGIS GIS&T Body of Knowledgecited by 1
  25. 2024Membership Inference Attacks and Privacy in Topic Modelingcited by 1
  26. 2023HICL: Hashtag-Driven In-Context Learning for Social Media Natural Language Understandingcited by 0
  27. 2023Boosting Summarization with Normalizing Flows and Aggressive Trainingcited by 0
  28. 2024CEV-LM: Controlled Edit Vector Language Model for Shaping Natural Language Generationscited by 0
  29. 2024VRDSynth: Synthesizing Programs for Multilingual Visually Rich Document Information Extractioncited by 0
  30. 2025Learning Extrapolative Sequence Transformations from Markov Chainscited by 0
  31. 2025Vec2Summ: Text Summarization via Probabilistic Sentence Embeddingscited by 0
  32. 2025Extrapolated Markov Chain Oversampling Method for Imbalanced Text Classificationcited by 0