Download and import the Math Notation Translator JSON
Save `math-notation-translator.json` and import it via the Vezz me extension popup.
Math Notation Translator Prompt: turn LaTeX equations into symbol glossaries and NumPy code.
Download the Math Notation Translator JSON preset for Vezz me. Highlight any LaTeX formula or ML equation on arXiv or Wikipedia to get a symbol glossary and Python/NumPy code.
Best fit
Best for ML engineers, data scientists, and CS students who prefer reading commented Python/NumPy array operations alongside mathematical notation.
On-screen walkthrough
How this looks on a real webpage.
Instead of switching tabs and rebuilding context, highlight the exact passage that slowed you down and press your shortcut (default: Ctrl+Shift+X or Cmd+Shift+X on macOS, fully customizable in settings).
1. Highlighted on page (arXiv HTML Paper — Scaled Dot-Product Attention)
Scaled Dot-Product Attention is computed as Attention(Q, K, V) = softmax(Q K^T / \sqrt{d_k}) V, where Q \in \mathbb{R}^{n \times d_k}, K \in \mathbb{R}^{m \times d_k}, and V \in \mathbb{R}^{m \times d_v}.
Ctrl+Shift+X“Give me a symbol glossary, array shapes, and a NumPy implementation of this equation.”
2. Vezz me on-screen answer overlay
1. **Symbol Glossary & Shapes**:
- `Q` `(n, d_k)`: Queries ($n$ query tokens, feature dim $d_k$).
- `K.T` `(d_k, m)`: Transposed Keys ($m$ key tokens).
- `Q @ K.T` `(n, m)`: Pairwise similarity score matrix.
- `sqrt(d_k)` (scalar): Dampens large dot products so softmax gradients don't vanish.
- `V` `(m, d_v)`: Values weighted by softmax probabilities -> output shape `(n, d_v)`.
2. **NumPy Equivalent**:
```python
def attention(Q, K, V):
d_k = Q.shape[-1]
scores = (Q @ K.T) / np.sqrt(d_k) # (n, m)
weights = np.exp(scores) / np.exp(scores).sum(axis=-1, keepdims=True) # (n, m)
return weights @ V # (n, d_v)
```
3. Suggested follow-up questions in thread
- “Where is the causal mask applied in decoder-only self-attention?”
- “Show this same equation using PyTorch `einops.einsum` notation.”
Importable Prompt Preset
Use this custom prompt in Vezz me.
Copy the system prompt below or download the .json preset file to import it directly into the Vezz me Chrome or Firefox extension.
Vezz me Custom Prompt Preset
Math Notation Translator
Math notation often leaves tensor dimensions and broadcast axes implicit; translating the equation into commented NumPy code forces every shape and reduction axis into the open.
Translate the selected mathematical equation or notation for a software engineer / STEM reader: 1) Symbol-by-Symbol Glossary: define every variable, subscript, superscript, and operator, including its scalar/vector/matrix shape, 2) Plain-English Intuition: in 2 sentences, explain what this formula computes and why each term is structured this way, 3) Python / NumPy Equivalent: write a clean 5–10 line Python/NumPy snippet that computes this exact formula with comments showing array shapes, and 4) Toy Numerical Walkthrough: plug in tiny numbers (2–3 elements) to show the arithmetic.Step-by-step workflow
How to run this workflow in place.
Highlight the equation AND the surrounding paragraph
Include the sentence before and after the formula so Vezz me captures the author's variable definitions.
Read the Symbol Glossary alongside the NumPy array shapes
Seeing `(n, d_k) @ (d_k, m) -> (n, m)` immediately resolves dimension confusion in linear algebra and ML papers.
Key details
Why this approach works better than switching tabs.
Frequently asked questions
Common questions about stem & ml equation preset.
Can I customize the preset to use PyTorch or JAX instead of NumPy?
Yes! Edit the imported preset in Vezz me and replace 'Python/NumPy' with 'PyTorch (`torch.Tensor` with `einops` notation)'.
Does this work on Wikipedia and arXiv HTML papers?
Yes—both arXiv HTML (`arxiv.org/html/`) and Wikipedia render selectable math text and LaTeX annotations.
What if a symbol was defined 5 pages earlier in the paper?
Vezz me will infer standard domain conventions (and flag if a symbol is context-dependent), or you can paste the earlier definition line into the prompt.
Related workflows & guides
Explore connected pages.
Ready to try this workflow on your own reading?
Install Vezz me free, highlight text on any webpage, and press your customizable shortcut (default: Ctrl+Shift+X or Cmd+Shift+X on Mac) to get an answer right beside the source.
