Yila AI

A literature review falls apart when notes, PDFs, and slides live in different places and nobody can see which sentence came from which paper. An evidence-traceable research agent is meant to sit inside an academic research workspace so that PDF analysis, figure drafts, and academic slides stay tied to the sources a researcher actually opened. This note is a practical checklist for that kind of workflow. It does not invent study results, and it does not attach fake citations to a product description.

What evidence-traceable should mean before you trust a draft

Traceable, in this setting, means a claim in a draft can be walked back to a passage, table, or figure in a source the researcher supplied or retrieved. It does not mean the software is a coauthor, and it does not mean every fluent sentence is correct. A useful academic research workspace makes the source visible next to the sentence, keeps the original file available, and lets a person edit the output. If a tool fills a bibliography with papers that were never retrieved, that is a failure of the workflow, not a shortcut. The check is simple: every reference in the draft should correspond to a document you can open.

Start the literature review from a question, not from a pile of tabs

Begin with one research question written in a sentence a colleague could disagree with. Add the constraints you already know: years, population, method, language, and what you will not cover. Then collect sources in a way you can audit. A paper link, a DOI you resolved yourself, or a PDF you uploaded is a better start than a vague prompt that says "summarize the field." Search results are a list to screen, not a finished review. For each candidate paper, record why it is in or out. That screening note is part of the method, even when the eventual article only shows the included set.

When the set is still messy, group papers by the question they answer rather than by the order you downloaded them. Typical groups are definition, measurement, prior empirical work, and disagreement. A short matrix with columns for question, method, data, and limitation is enough. The matrix is a checklist, not a statistical meta-analysis. Do not turn it into pooled numbers unless you designed a meta-analysis and have the studies in front of you.

PDF analysis without losing the page

Full-text reading is where generic chat windows tend to drift. They compress a paper into smooth prose and drop the caveat that lived in a footnote or a limitations section. PDF analysis in a research workspace should keep the page, the section, and the table identity available when you ask for a summary. Practical checks:

• Ask for the stated research question and compare it with the abstract you can see.
• Ask for the sample, the outcome, and the limitation in separate lines, then confirm each line against the PDF.
• If a number appears, find the table or paragraph it came from before you reuse it.
• If the tool cannot point at the file you uploaded, treat the summary as unverified notes, not as a citation.

Highlighting and export should remain editable. A locked "final" summary that you cannot correct is less useful than a rough outline you can fix. Private-by-default handling matters here because unpublished manuscripts and review PDFs are not public web pages.

Figures that argue one comparison

Scientific figures in a paper or a talk should carry one comparison a reader can name. Before you ask for a chart, write the sentence the chart must support, the unit on each axis, and the source table. A workspace that can draft a figure from a table you uploaded is helpful only if you can rebuild the chart from the same table later. Keep the code or the sheet attached to the figure. Decorative icons and stock metaphors do not belong in a results figure. If you do not have data, do not invent a results chart. A schematic of your own workflow is fine when it is labeled as a schematic of a process, not as empirical evidence.

From papers to academic slides

Academic slides are a compression of the review, not a second paper with new claims. A reasonable paper-to-slides workflow moves in this order: question, why it matters in one sentence, how you searched and screened, what the sources agree on, what they contradict, what you are not claiming, and what you would need next. Each slide should point at a source you can open. Titles should state the point, not the topic label "Background." If a slide makes a numeric claim, the same number should exist in your notes with a file and a location. Cut any slide that only restates a slogan.