Narrow your topic.
Screen the papers.
Write the review yourself.
Lit Mind Maps is a student research assistant, not a ghostwriter. It challenges a rough topic through a guided conversation grounded in real Semantic Scholar evidence — too broad, too narrow, or ready to defend — then builds you a screening table and a literature-space + gap map for exactly that question. You still read the full papers and write the review, so it stays fully within your university's research-integrity policy.
Tell us your rough topic
No need to have a research question yet — “social media and teen mental health” is enough to start.
We challenge your scope
A guided back-and-forth, grounded in live paper counts and sample titles, tells you plainly when you're too broad or too narrow — and asks the questions that get you to a defensible angle.
Get your screening table
A table of the papers that match your narrowed question, ready for you to relevance-tag as you read the full texts through your library.
See the space & the gaps
A literature-space tree shows the branches you could pull into your study; a coverage matrix shows what's studied and what's genuinely open — you write the review from there.
A research assistant, not a ghostwriter
One guided workflow: narrow your topic through conversation, get a screening table, then see the literature space and its gaps — all from one account.
Narrowing chat
A back-and-forth conversation, grounded in real evidence, that challenges a topic that's too broad or too narrow until you reach a defensible research question.
Screening table
The papers matching your narrowed question, with the metadata you need to triage relevance — you still read the full texts and cite them yourself.
Literature-space & gap map
See the branches of the field you could pursue, and a coverage matrix of what's studied versus genuinely open.
Built to keep the review yours
AI literature-review generators draft the synthesis for you — which is exactly what most university research-integrity policies don't allow. Lit Mind Maps stops short of that line on purpose.
Real papers only
Sourced live from the Semantic Scholar Academic Graph — titles, authors, venues, years, and abstracts feed every step.
Never drafts your review
The AI only reflects evidence and asks questions — it never picks your research question or writes review prose for you.
Challenges your scope
Too broad, too narrow, or genuinely unclear — the assistant says so plainly, with the paper counts and sample titles to back it up.
You do the screening
Relevance-tag papers yourself in a table built from your narrowed question — the judgment calls stay with you.
Visual, not a black box
A literature-space tree and a gap coverage matrix, so you can see the reasoning behind every suggestion.
Defensible to your supervisor
Leave the conversation with a research question you understand and can explain — not one an AI handed you.
Why students choose Lit Mind Maps
AI literature-review tools (Elicit-, SciSpace-, AnswerThis-style) are fast, but drafting your synthesis for you is exactly the kind of AI use most universities' academic-integrity policies flag. Lit Mind Maps is built to stay on the right side of that line.
| What matters | AI review-writing tools | Manual review | Lit Mind Maps |
|---|---|---|---|
| Who writes the review | ✗ the AI drafts it | ✓ you | ✓ you, always |
| Research-integrity safe by design | ✗ often a grey area | ✓ | ✓ screening + scoping only |
| Challenges a too-broad/too-narrow topic | rarely | your supervisor does | ✓ every turn, with evidence |
| Real, verifiable papers | mostly | ✓ | ✓ via Semantic Scholar |
| Time to a screening table | minutes | days–weeks | minutes |
| Gaps → research questions | sometimes | manual | ✓ visual coverage matrix |
Start narrowing your topic
Free to explore — no credit card needed. Talk through your topic, get your screening table, and see the gap map for your narrowed question.
Create my free account