Pith Number

pith:VBTBECI4

pith:2026:VBTBECI43ZLD4XJICIQQU46PZX

not attested not anchored not stored refs pending

Generative Refinement Networks for Visual Synthesis

Bingyue Peng, Jiahuan Wang, Jian Han, Jinlai Liu, Zehuan Yuan

Generative Refinement Networks combine near-lossless quantization with global refinement to surpass diffusion and autoregressive models in visual synthesis.

arxiv:2604.13030 v2 · 2026-04-14 · cs.CV

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\pithnumber{VBTBECI43ZLD4XJICIQQU46PZX}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

On the ImageNet benchmark, GRN establishes new records in image reconstruction (0.56 rFID) and class-conditional image generation (1.81 gFID). We also scale GRN to more challenging text-to-image and text-to-video generation, delivering superior performance on an equivalent scale.

C2weakest assumption

That the Hierarchical Binary Quantization is theoretically near-lossless and that the global refinement mechanism corrects errors without introducing new accumulation problems or requiring post-hoc tuning that affects the reported metrics.

C3one line summary

GRN uses hierarchical binary quantization and entropy-guided refinement to set new ImageNet records of 0.56 rFID for reconstruction and 1.81 gFID for class-conditional generation while releasing code and models.

Cited by

1 paper in Pith

Beyond Token-Level Cross-Entropy: Fr\'echet Distributional Post-Training for Autoregressive Image Generation

Receipt and verification

First computed	2026-07-08T01:19:12.859218Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

a86612091cde563e5d2812210a73cfcdf08fd236a37537eb4b2877df9e556ca5

Aliases

arxiv: 2604.13030 · arxiv_version: 2604.13030v2 · doi: 10.48550/arxiv.2604.13030 · pith_short_12: VBTBECI43ZLD · pith_short_16: VBTBECI43ZLD4XJI · pith_short_8: VBTBECI4

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/VBTBECI43ZLD4XJICIQQU46PZX \
  | 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: a86612091cde563e5d2812210a73cfcdf08fd236a37537eb4b2877df9e556ca5

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "977f9bb339fa6c6087184224f4f8e59ed2abb726d43fe819f15aecea94e8ea88",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-14T17:59:03Z",
    "title_canon_sha256": "882a87b9ada1a0488dcca7fa5e5ec821c4a407cfbb87e48990287d81c6e2d0f4"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.13030",
    "kind": "arxiv",
    "version": 2
  }
}