{
  "schemaVersion": 1,
  "slug": "evoformer",
  "title": "Exchange alignment and residue-pair information",
  "className": "EvoformerCoupling",
  "question": "How do sequence and pair representations interact before structure is produced?",
  "description": "Inspect pair-biased MSA attention, outer-product mean and outgoing triangle multiplication in a reduced Evoformer coupling subsystem.",
  "category": "Alternative architectures",
  "tags": [
    "AlphaFold2",
    "Evoformer",
    "Protein structure",
    "MSA",
    "Triangle update"
  ],
  "curator": "TensorViz",
  "attribution": "Original TensorViz teaching example. PyTorch provides the underlying operators.",
  "license": "No separate redistribution license has been declared for these project examples.",
  "limitations": "Untrained coupling subsystem, not a complete Evoformer block or AlphaFold2. Omits MSA column attention/transition, incoming triangle multiplication, triangle attention, masks, dropout, templates, extra-MSA stack, recycling and the structure module. Synthetic continuous inputs are already-embedded features. Pair channels are not distances and no protein coordinates, confidence or biological accuracy are predicted.",
  "openingStep": "outer",
  "provenance": {
    "capturedAt": "2026-09-17T07:00:42.198081+00:00",
    "productRevision": "cf0ab1c9c58c1dc640235b742fa032cade00b43c",
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              4,
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    "outcome": "passed",
    "outputShape": [
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      4,
      4
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    "method": "TensorViz multifile projection and isolated execution worker",
    "scope": "Evoformer coupling subsystem on synthetic MSA and pair tensors. Sequence/residue permutation, explicit outer-product and triangle sums, and cross-stream gradient checks.",
    "numericalChecks": [
      "Reordering aligned sequences preserves pair outputs; relabeling residues permutes both pair axes consistently",
      "Outer-product mean matches an explicit per-sequence, per-residue-pair calculation",
      "Outgoing triangle multiplication matches an explicit sum over shared third residues k",
      "An MSA edit changes pair features; gradients flow through both streams and the pair-to-attention bias"
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  "steps": [
    {
      "id": "msa",
      "target": "msa_row.pair_bias",
      "title": "Let pair features bias each alignment row",
      "note": "The multiple sequence alignment has one row per aligned sequence and one column per residue position. Each row attends along residues; a projected pair representation adds the same residue-pair bias to every row’s attention scores."
    },
    {
      "id": "outer",
      "target": "outer_product.project",
      "title": "Transfer alignment evidence back into residue pairs",
      "note": "Two projections of the updated MSA form an outer product for each residue pair. Averaging over the three aligned sequences yields nine intermediate features, projected into four pair channels."
    },
    {
      "id": "triangle",
      "target": "triangle.project",
      "title": "Update a pair through shared third residues",
      "note": "For pair (i,j), outgoing triangle multiplication combines gated features from (i,k) and (j,k), summing over k. LayerNorm, projection and an output gate produce the pair update. This operation exchanges relational features; it does not directly construct a geometric triangle."
    },
    {
      "id": "transition",
      "target": "pair_transition.down",
      "title": "Refine pair channels before later structure reasoning",
      "note": "A pointwise feed-forward transition follows the triangle update. The complete AlphaFold2 system repeats a much larger Evoformer stack and passes its representations into a separate structure module. That structure module is outside this example."
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  "milestone": {
    "name": "AlphaFold2 · Evoformer coupling",
    "year": 2021,
    "kind": "Component",
    "fidelity": "Three aligned sequences, four residue positions, eight MSA channels and four pair channels. Implements reduced supplementary Algorithms 7, 10 and 11 plus a pair transition; MSA row attention uses two heads.",
    "papers": [
      {
        "title": "Highly accurate protein structure prediction with AlphaFold",
        "url": "https://www.nature.com/articles/s41586-021-03819-2"
      },
      {
        "title": "AlphaFold supplementary methods · Evoformer algorithms",
        "url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41586-021-03819-2/MediaObjects/41586_2021_3819_MOESM1_ESM.pdf"
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