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Text Generation

Introduction

Papers

Deep Reinforcement Learning Based

  1. Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation. ACL 2019. [PDF]

Neural Network Based

  1. Towards Generating Long and Coherent Text with Multi-Level Latent Variable Models. ACL 2019. [PDF]
  2. Sentence-Level Content Planning and Style Specification for Neural Text Generation. EMNLP 2019. [PDF]
  3. Denoising-based Sequence-to-Sequence Pre-training for Text Generation. EMNLP 2019. [PDF]
  4. A Graph-to-Sequence Model for AMR-to-Text Generation. ACL 2018. [PDF]
  5. Controlling Global Statistics in Recurrent Neural Network Text Generation. AAAI 2018. [PDF]
  6. Long Text Generation via Adversarial Training with Leaked Information. AAAI 2018. [PDF]
  7. Order-Planning Neural Text Generation From Structured Data. AAAI 2018. [PDF]
  8. Table-to-text Generation by Structure-aware Seq2seq Learning. AAAI 2018. [PDF]

Others Based

  1. Data-to-Text Generation with Content Selection and Planning. AAAI 2019. [PDF]
  2. Hierarchical Encoder with Auxiliary Supervision for Table-to-text Generation: Learning Better Representation for Tables. AAAI 2019. [PDF]
  3. ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexicallyconstrained Neural Machine Translation. AAAI 2019. [PDF]
  4. Differentiated Distribution Recovery for Neural Text Generation. AAAI 2019. [PDF]
  5. A Topic Augmented Text Generation Model: Joint Learning of Semantics and Structural Features. EMNLP 2019. [PDF]
  6. ARAML: A Stable Adversarial Training Framework for Text Generation. EMNLP 2019. [PDF]
  7. Deep Copycat Networks for Text-to-Text Generation. EMNLP 2019. [PDF]
  8. Enhancing AMR-to-Text Generation with Dual Graph Representations. EMNLP 2019. [PDF]
  9. Enhancing Neural Data-To-Text Generation Models with External Background Knowledge. EMNLP 2019. [PDF]
  10. Enhancing Recurrent Variational Autoencoders with Mutual Information Estimation for Text Generation. EMNLP 2019. [PDF]
  11. Implicit Deep Latent Variable Models for Text Generation. EMNLP 2019. [PDF]
  12. Long and Diverse Text Generation with Planning-based Hierarchical Variational Model. EMNLP 2019. [PDF]
  13. Modeling Graph Structure in Transformer for Better AMR-to-Text Generation. EMNLP 2019. [PDF]
  14. MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance. EMNLP 2019. [PDF]
  15. Neural data-to-text generation: A comparison between pipeline and end-to-end architectures. EMNLP 2019. [PDF]
  16. Select and Attend: Towards Controllable Content Selection in Text Generation. EMNLP 2019. [PDF]
  17. Table-to-Text Generation with Effective Hierarchical Encoder on Three dimensions (Row, Column and Time). EMNLP 2019. [PDF]
  18. Autoregressive Text Generation beyond Feedback Loops. EMNLP 2019. [PDF]

Metrics for Text Generation

  1. A Cross-Domain Transferable Neural Coherence Model. ACL 2019. [PDF]
  2. Sentence Mover's Similarity Automatic Evaluation for Multi-Sentence Texts. ACL 2019. [PDF]

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