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pith:RYU2AZN2

pith:2026:RYU2AZN2J4GJBV7FJ36RS2QDRT
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Autoregressive Visual Generation Needs a Prologue

Bowen Zheng, Colin Zhang, Guang Yang, Tianyang Hu, Weijian Luo

Prepending a small set of prologue tokens trained only on AR loss decouples generation from reconstruction in autoregressive image models.

arxiv:2605.06137 v2 · 2026-05-07 · cs.CV · cs.AI · cs.LG

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4 Citations open
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Claims

C1strongest claim

On ImageNet 256x256, Prologue-Base reduces gFID from 21.01 to 10.75 without classifier-free guidance while keeping reconstruction almost unchanged; Prologue-Large reaches a competitive rFID of 0.99 and gFID of 1.46 using a standard AR model without auxiliary semantic supervision.

C2weakest assumption

The assumption that training prologue tokens exclusively with AR CE loss will not interfere with the visual tokens' reconstruction quality and that the ELBO formalization supports the decoupled optimization.

C3one line summary

Prologue introduces dedicated prologue tokens to decouple generation and reconstruction in AR visual models, significantly improving generation FID scores on ImageNet while maintaining reconstruction quality.

Receipt and verification
First computed 2026-06-01T01:03:54.500915Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

8e29a065ba4f0c90d7e54efd196a038cf99ad4c7f7658b6b29ad57588600595e

Aliases

arxiv: 2605.06137 · arxiv_version: 2605.06137v2 · doi: 10.48550/arxiv.2605.06137 · pith_short_12: RYU2AZN2J4GJ · pith_short_16: RYU2AZN2J4GJBV7F · pith_short_8: RYU2AZN2
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/RYU2AZN2J4GJBV7FJ36RS2QDRT \
  | 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: 8e29a065ba4f0c90d7e54efd196a038cf99ad4c7f7658b6b29ad57588600595e
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-07T12:35:51Z",
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