EagleW/PaperRobot
A deep learning system that incrementally generates scientific paper drafts including titles, abstracts, and conclusions from prior research.
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PaperRobot is a research system for automated scientific paper generation published at ACL 2019. It uses an incremental approach to produce paper sections—titles, abstracts, conclusions, and future work—from existing scientific literature. The model employs attention mechanisms and memory networks with PyTorch, trained on PubMed datasets containing over 875,000 training pairs for title-to-abstract and abstract-to-conclusion generation tasks.
Frequently asked
- What is EagleW/PaperRobot?
- A deep learning system that incrementally generates scientific paper drafts including titles, abstracts, and conclusions from prior research.
- Is PaperRobot open source?
- Yes — EagleW/PaperRobot is open source, released under the MIT license.
- What language is PaperRobot written in?
- EagleW/PaperRobot is primarily written in Python.
- How popular is PaperRobot?
- EagleW/PaperRobot has 479 stars on GitHub.
- Where can I find PaperRobot?
- EagleW/PaperRobot is on GitHub at https://github.com/EagleW/PaperRobot.