Undermind for Web

Overview: modernizing scholarly discovery

Undermind is a web application built to improve academic research by systematically reading and analyzing large numbers of scholarly papers. It leverages state-of-the-art language models to pull out exact answers to user queries and emulates the step-by-step search behavior a researcher would use.

How it finds more relevant material than a typical search

Instead of returning static search results, Undermind adjusts its approach as it ingests documents, refining queries and prioritizing new leads. This iterative strategy helps it deliver more complete and pertinent findings across disciplines such as quantum computing and artificial intelligence. The system is also able to detect when it has collected the essential literature for a query, focusing results to avoid noise.

Data coverage and access model

Undermind operates on a subscription basis and obtains its metadata and papers from the Semantic Scholar collection, which comprises more than 200 million research articles. This large, curated index gives researchers a dependable foundation for literature discovery.

Planned expansions

Future updates will add full-text discovery capabilities, broadening the tool’s usefulness for in-depth investigations and complex review tasks.

Core capabilities

• Adaptive querying that refines search tactics as new documents are analyzed
• Precise extraction of answers tailored to user questions
• Broad subject coverage spanning multiple research areas
• Ability to determine when a search has reached sufficient completeness
• Subscription-based access integrated with the Semantic Scholar corpus
• Upcoming support for full-text retrieval to enhance deep-dive research