Scholar-Agent – Automate Literature Benchmarking and Metric Extraction

Summary: Scholar-Agent automates extraction of benchmark metrics like RMSE and ATE from academic papers, linking large paper databases with local experimental data. It uses LangGraph architecture and Docling’s PDF parsing to streamline literature reviews and SOTA comparisons.

What it does

It parses lengthy PDFs to extract key performance metrics and compares them with user data, automating the benchmarking process using LLM and parsing technologies.

Who it's for

Researchers needing to efficiently compare their experimental results with state-of-the-art academic papers.

Why it matters

It reduces the time and effort spent manually reviewing papers to find relevant benchmarking metrics.