Identifying, Summarizing, and Analyzing Research Papers
- Data Collection: Gather research papers in the specified domain. This could involve using APIs of research databases like PubMed, arXiv, etc.
- Paper Classification: Use a machine learning model to classify papers as either seminal or state-of-the-art. This could be based on factors like citation count, recency, etc.
- Summarization: Use a language model to generate summaries of the papers. This could involve both extractive and abstractive summarization techniques.
- Dataset Identification: Use NLP techniques to identify mentions of benchmark datasets in the papers.
- Expert Identification: Analyze authorship and citation data to identify leading experts in the domain.