Read papers in other fields whenever possible.

Read papers from other conferences whenever possible.

Read as many papers as possible.

• What I Have Read
  • Slides
    • Summarization
    • Presentation
    • Paper slides
    • Notes
  • Summarization Papers
  • Unsupervised
  • Cross-Lingual
  • Meta Learning Papers
  • Graph Neural Networks (GNN)
  • Generative Adversarial Networks (GAN)
  • Knowledge Distillation
  • Pre-train Based
  • Multi Modal
  • Natural Language Generation
  • Imitation Learning
  • Decode
  • Textual Adversarial Attack and Defense

• Summarization
• 文本摘要简述
• ACL19 Summarization

• Event Extraction
• Meta Learning
• Advanced pre-training language models a brief introduction
• Graph Neural Networks
• Knowledge Distillation
• Non-Autoregressive Decoding

• ACL19-Dynamically Fused Graph Network for Multi-hop Reasoning
• NAACL19-Linguistic Knowledge and Transferability of Contextual Representations
• NAACL19-Text Generation from Knowledge Graphs with Graph Transformers
• The Curious Case of Neural Text Degeneration
• EMNLP18-Multi-Domain Neural Machine Translation with Word-Level Domain Context Discrimination
• EMNLP18-Commonsense for Generative Multi-Hop Question Answering Tasks
• IJCAI18-Commonsense Knowledge Aware Conversation Generation with Graph Attention
• AAAI18-Emotional Chatting Machine Emotional Conversation Generation with Internal and External Memory
• EMNLP18-Learning Neural Templates for Text Generation
• ACL18-Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders
• ACL17-Semi-Supervised QA with Generative Domain-Adaptive Nets
• ACL17-Deep Multitask Learning for Semantic Dependency Parsing

• GAN in Text Generation
• Boosting
• HMM
• The Maximum Entropy Model