EagleW/PaperRobot

Code for PaperRobot: Incremental Draft Generation of Scientific Ideas

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Combines relation extraction and sequence generation in a two-stage pipeline: link prediction over knowledge graphs extracted from PubMed identifies relevant entities and facts, while neural generation models produce paper sections (abstracts, conclusions, titles) conditioned on these predicted relations. Built on PyTorch with NetworkX for graph operations, the system trains on paired PubMed data covering both entity linking and text generation tasks.

483 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

483

Forks

131

Language

Python

License

MIT

Last pushed

Mar 09, 2024

Commits (30d)

0

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