This repository is a curated reading list for text generation, maintained by the Tsinghua Natural Language Processing Group. It serves as a comprehensive resource for researchers and practitioners interested in the field, providing categorized papers, datasets, and tools to advance text generation research.

How It Works

The list is organized by sub-fields within text generation, including Seq2Seq, Variational Autoencoders, Generative Adversarial Networks, Reinforcement Learning, and Knowledge-Based methods. It links to seminal papers, relevant datasets (e.g., ROCStories, VIST, WritingPrompts), and popular text generation toolkits (e.g., Texar, Textgen).

Quick Start & Requirements

This repository is a reading list and does not involve direct installation or execution. Users can browse the categorized links to papers, datasets, and tools.

Highlighted Details

• Extensive categorization of text generation research papers.
• Links to key datasets for various text generation tasks.
• Inclusion of prominent text generation toolkits and their code repositories.
• Citations provided for many papers, indicating their impact.

Maintenance & Community

Maintained by the Tsinghua Natural Language Processing Group. Suggestions for additions or improvements are welcomed.

Licensing & Compatibility

The repository itself is a collection of links and does not have a specific license. Individual linked resources may have their own licenses.

Limitations & Caveats

As a reading list, it does not provide code implementations or direct access to datasets; users must follow the provided links. The list's comprehensiveness is dependent on ongoing community contributions and maintenance.