prereq-probe

To identify prerequisite concepts in an academic paper, ingest the paper content to scan for non-universal specialized foundations. The tool extracts these concepts and builds a hierarchical dependency tree to map what must be known first.

A knowledge map for paper reading is a generated file that encodes concept levels and prerequisite dependencies. It probes for non-universal specialized foundations, recording what the user knows to tailor and control the depth of downstream explanations.

Build a dependency tree by ingesting academic paper content to extract non-universal concepts. The system maps these prerequisites hierarchically, showing exactly what specialized knowledge must be understood before tackling the paper.

Concept probing is designed for papers with specialized foundations beyond universal CS and ML knowledge. Papers assuming only universal knowledge do not require this prerequisite mapping, as the tool targets non-universal gaps.

A knowledge map controls explanation depth by recording what the user already knows during a guided probing phase. It encodes concept levels and dependencies, enabling downstream skills to tailor explanations specifically to your knowledge gaps.

Automated prerequisite mapping is limited to non-universal specialized concepts identified within the ingested text. It relies on the paper content provided and does not account for entirely unmentioned foundational knowledge or universal CS and ML concepts.