Tracking your scientific niche?
AI/lluminator
Technology
Filtering Scientific Literature
Retrieval Augmented Generation (RAG)
AI/lluminator uses the RAG model to filter the scientific literature. This model is based on the idea of using a retrieval model to find the most relevant papers, and then using a generation model to summarize the papers. This way, you can get the most relevant information from the scientific literature without having to read the entire paper.
The RAG model is trained on a large dataset of scientific papers and is able to generate summaries that are both accurate and concise. This makes it an ideal tool for keeping track of the latest research in your field.
A custom Embedding Model
AI/lluminator uses a custom embedding model to represent the scientific papers in a high-dimensional space. This allows the model to capture the semantic meaning of the papers and to find the most relevant papers based on their content.
The embedding model is trained on a large dataset of scientific papers and is able to capture the relationships between different papers. This makes it an ideal tool for filtering the scientific literature and for finding the most relevant papers in your field.