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pith:QDRDPX6V

pith:2026:QDRDPX6VG2XO2EQ7GT4NP2GWOH
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Residual Stream Duality in Modern Transformer Architectures

Yifan Zhang

The residual stream in Transformers is equivalent to causal short sliding-window attention when interpreted over layer depth instead of sequence positions.

arxiv:2603.16039 v2 · 2026-03-17 · cs.LG · cs.AI · cs.CL

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Claims

C1strongest claim

a causal depth-wise residual attention read is exactly the same local operator as causal short sliding-window attention (ShortSWA), except written over depth rather than over sequence. This is the core residual stream duality behind Transformer².

C2weakest assumption

That treating layer index as an ordered variable and reinterpreting fixed residual addition as causal depth-wise attention produces a meaningful and actionable operator equivalence, even though the paper states operator-level duality does not imply systems-level symmetry.

C3one line summary

Residual stream addition over depth is the same local operator as causal short sliding-window attention over sequence positions.

Formal links

1 machine-checked theorem link

Cited by

1 paper in Pith

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First computed 2026-05-17T23:38:59.635560Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

80e237dfd536aeed121f34f8d7e8d671f4b78230b02122d902ca88241561836d

Aliases

arxiv: 2603.16039 · arxiv_version: 2603.16039v2 · doi: 10.48550/arxiv.2603.16039 · pith_short_12: QDRDPX6VG2XO · pith_short_16: QDRDPX6VG2XO2EQ7 · pith_short_8: QDRDPX6V
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/QDRDPX6VG2XO2EQ7GT4NP2GWOH \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 80e237dfd536aeed121f34f8d7e8d671f4b78230b02122d902ca88241561836d
Canonical record JSON
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    "primary_cat": "cs.LG",
    "submitted_at": "2026-03-17T00:56:29Z",
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