Pith Number

pith:GDCQ5IT2

pith:2026:GDCQ5IT2DPZZVVSS6XRUJC7UOL

not attested not anchored not stored refs pending

One-Step Generative Modeling via Wasserstein Gradient Flows

Emmanuel J. Cand\`es, Jiaqi Han, Puheng Li, Qiushan Guo, Renyuan Xu, Stefano Ermon

W-Flow achieves one-step ImageNet 256x256 generation at 1.29 FID by training a neural network to compress a Wasserstein gradient flow.

arxiv:2605.11755 v2 · 2026-05-12 · cs.LG · cs.CV · stat.ML

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\pithnumber{GDCQ5IT2DPZZVVSS6XRUJC7UOL}

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Record completeness

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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

W-Flow sets a new state of the art for one-step ImageNet 256×256 generation, achieving 1.29 FID, with improved mode coverage and domain transfer. Compared to multi-step diffusion models with similar FID scores, our method yields approximately 100× faster sampling.

C2weakest assumption

The finite-sample training dynamics converge to the continuous-time distributional dynamics under suitable assumptions. The abstract does not specify what those assumptions are or how restrictive they become for high-dimensional image data.

C3one line summary

W-Flow achieves state-of-the-art one-step ImageNet 256x256 generation at 1.29 FID by training a static neural network to follow a Wasserstein gradient flow that minimizes Sinkhorn divergence, delivering roughly 100x faster sampling than comparable multi-step models.

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-28T01:04:42.241787Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

30c50ea27a1bf39ad652f5e3448bf472de9df646ee9eea9bfaadf0cc6be1a80a

Aliases

arxiv: 2605.11755 · arxiv_version: 2605.11755v2 · doi: 10.48550/arxiv.2605.11755 · pith_short_12: GDCQ5IT2DPZZ · pith_short_16: GDCQ5IT2DPZZVVSS · pith_short_8: GDCQ5IT2

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/GDCQ5IT2DPZZVVSS6XRUJC7UOL \
  | 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: 30c50ea27a1bf39ad652f5e3448bf472de9df646ee9eea9bfaadf0cc6be1a80a

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "10abfdef1b415dff3ab1aa5ed9c64aca67dd2a3207110c238a4689c3cfa17cac",
    "cross_cats_sorted": [
      "cs.CV",
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-12T08:29:44Z",
    "title_canon_sha256": "13d37a7846389cfcca67d31a522784abbd975f8b5b32ab3b1e014d8df87ba55f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.11755",
    "kind": "arxiv",
    "version": 2
  }
}