Tutorial · 8 min read
How to Turn a Research Paper into an Explainer Video (Attention Is All You Need)
A step-by-step tutorial for converting dense academic papers into accurate, editable explainer videos using Vyakhya's open-source multi-agent AI video generator.
Why most AI video generators fail on research papers
Broad AI video generators are optimized for marketing clips and social snippets. Feed them a dense arXiv PDF full of equations, citations, and multi-column figures and you get a shallow paraphrase — bullet points read out over stock footage. That's fine for a product teaser, useless for a graduate-level explainer.
Vyakhya was built for the opposite end of that spectrum: a multi-agent engine that reads the paper the way a human would — extracting math, resolving references, and planning a scene-by-scene walkthrough — then renders it locally on your own machine.
What we'll build
In this walkthrough we'll convert Attention Is All You Need (Vaswani et al., 2017) — the paper that introduced the Transformer — into a ~10-minute explainer video with animated attention diagrams, narrated derivations, and cited figures.
Step 1 — Prepare the paper
Download the PDF from arXiv. Vyakhya works best on the publisher/preprint PDF (not a screenshot or scanned copy) because the ingestion agent uses the embedded text layer to preserve equations and citations.
Step 2 — Ingest with Vyakhya
Start Vyakhya locally and drop the PDF into the new-project panel. The ingestion agent parses the document into sections, pulls out figures and tables, and builds a citation graph. For Attention Is All You Need you'll see the six-encoder / six-decoder architecture surfaced as a first-class object you can point the narration at.
Step 3 — Review the generated outline
The planner agent proposes a scene list — typically: motivation, prior work (RNNs and convolutions), scaled dot-product attention, multi-head attention, positional encoding, results, and takeaways. Every scene is editable: reorder, merge, split, or rewrite the beat in plain English.
Step 4 — Refine visuals and narration
Each scene has three panes: the narration script, the visual (diagram, equation render, or figure lift from the paper), and the timing. Because Vyakhya keeps the source PDF in context, you can ask it to "re-derive equation 1 with intermediate steps" or "swap the architecture diagram for figure 2" and it stays grounded in the paper.
Step 5 — Render locally
Hit render. Vyakhya composites the scenes, generates voice-over, and writes an MP4 to your project folder. Nothing leaves your machine — useful when the paper is under submission or behind an NDA.
Where this beats generic AI video generators
- Preserves equations as rendered LaTeX, not screenshots.
- Cites figures inline and reuses the paper's own diagrams.
- Editable at every layer — outline, script, visuals, timing.
- Self-hosted: no per-minute cloud pricing, no data leaving your machine.
Try it on your own paper
Vyakhya is open source. Clone the repo, point it at a PDF, and you'll have a first draft video in the time it would take to write the abstract.