Contextualized Literature-based Discovery
1 papers with code • 0 benchmarks • 0 datasets
Given a seed term (e.g., a task or method in NLP, or a disease in biomedicine) and corresponding background (e.g., challenges for a given task), the model's aim is to generate idea suggestions. The Contextual Literature-Based Discovery (CLBD) will take two different formulations of C-LBD: idea sentence generation and idea node prediction.
Benchmarks
These leaderboards are used to track progress in Contextualized Literature-based Discovery
Most implemented papers
SciMON: Scientific Inspiration Machines Optimized for Novelty
eaglew/clbd
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We explore and enhance the ability of neural language models to generate novel scientific directions grounded in literature.
