Scientific Summarization & Simplification
Purpose
Generate concise, accurate summaries of scientific papers, educational materials, and complex technical documents.
Key Datasets
- PubMed Summarization (ccdv/pubmed-summarization): Article-abstract pairs for biomedical summarization
- LearningQ (AngusGLChen/LearningQ): TED-Ed (7K) + Khan Academy (223K) educational QA for learning-oriented summarization
Protocol
- Document analysis — Identify paper structure (IMRaD, review, case report)
- Key claim extraction — Extract main findings, methods, and conclusions
- Audience calibration — Adjust complexity to target audience (expert, student, public)
- Summary generation — Structured summary with key takeaways