deep-literature-review

To automate an in-depth literature review, you can use a multi-hop discovery process that searches related papers across databases and generates detailed reading notes with verbatim quotes and locators. This produces a comprehensive survey report identifying consensus, tensions, and research gaps.

The best way to ensure source fidelity when creating deep reading notes is to apply a verification process that checks note fidelity against original source materials. An optional double-reader mode provides an extra layer of verification for critical academic papers.

Multi-hop discovery for finding related academic papers works by automatically exploring references and citations across multiple databases. This iterative search process expands the literature pool to build a comprehensive evidence base for the final synthesis and reporting stage.

Yes, you can render math formulas correctly in markdown literature survey reports by applying math rendering checks during note generation. This ensures that mathematical notations from source academic papers are accurately preserved in the final markdown output.

Yes, you need literature search tools to generate a comprehensive survey report, as the deep reading and multi-hop discovery process relies on them to pull academic papers. You provide a markdown document of pulled literature to initiate the review and synthesis workflow.