Pith Number

pith:43XJWIZM

pith:2026:43XJWIZMTQALRDFTVUWDKTD73L

not attested not anchored not stored refs resolved

AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation

Guian Fang, Han Cai, Mike Zheng Shou, Song Han, Weijia Mao, Yuchao Gu, Yuxin Jiang

AnyFlow distills video diffusion models to match few-step consistency performance while preserving scaling as sampling steps increase.

arxiv:2605.13724 v1 · 2026-05-13 · cs.CV · cs.AI

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\usepackage{pith}
\pithnumber{43XJWIZMTQALRDFTVUWDKTD73L}

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Record completeness

1 Bitcoin timestamp

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

AnyFlow achieves performance matches or surpasses consistency-based counterparts in the few-step regime, while scaling with sampling step budgets.

C2weakest assumption

That learning flow-map transitions over arbitrary intervals via backward simulation will avoid introducing new discretization or exposure biases that undermine the original ODE scaling behavior.

C3one line summary

AnyFlow enables any-step video diffusion by distilling flow-map transitions over arbitrary time intervals with on-policy backward simulation.

References

49 extracted · 49 resolved · 17 Pith anchors

[1] Wan: Open and Advanced Large-Scale Video Generative Models 2025 · arXiv:2503.20314

[2] Cosmos World Foundation Model Platform for Physical AI 2025 · arXiv:2501.03575

[3] HunyuanVideo: A Systematic Framework For Large Video Generative Models 2024 · arXiv:2412.03603

[4] CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer 2024 · arXiv:2408.06072

[5] LTX-Video: Realtime Video Latent Diffusion 2024 · arXiv:2501.00103

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T02:44:16.626721Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e6ee9b232c9c00b88cb3ad2c354c7fdaca6807416475361653ff503a956678b1

Aliases

arxiv: 2605.13724 · arxiv_version: 2605.13724v1 · doi: 10.48550/arxiv.2605.13724 · pith_short_12: 43XJWIZMTQAL · pith_short_16: 43XJWIZMTQALRDFT · pith_short_8: 43XJWIZM

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/43XJWIZMTQALRDFTVUWDKTD73L \
  | 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: e6ee9b232c9c00b88cb3ad2c354c7fdaca6807416475361653ff503a956678b1

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "0d17f10040eef6d0c79d044c96895c686b2383ca26c9d6d5a87778a88fc26ad6",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T16:06:34Z",
    "title_canon_sha256": "53af612fb312196dd64b2d9c814636fb81cf9acc283cd82a90f27d488622547e"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13724",
    "kind": "arxiv",
    "version": 1
  }
}