Pith Number

pith:IPPTRWIX

pith:2025:IPPTRWIXLE5FPQTJBUPLGYMZ5T

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HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer

Bo Zhao, Fengbin Gao, Fuchen Long, Jianzhuang Pan, Jingwen Chen, Kai Yu, Peihan Xu, Qi Cai, Rui Tian, Siyu Wang, Tao Mei, Ting Yao, Wenxuan Chen, Yang Chen, Yehao Li, Yiheng Zhang, Yimeng Wang, Yingwei Pan, Yi Peng, Zhaofan Qiu, Zijian Gong, Ziwei Feng

HiDream-I1 deploys a 17B-parameter sparse Diffusion Transformer that delivers state-of-the-art images in seconds.

arxiv:2505.22705 v1 · 2025-05-28 · cs.CV · cs.MM

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\usepackage{pith}
\pithnumber{IPPTRWIXLE5FPQTJBUPLGYMZ5T}

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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

HiDream-I1 ... achieves state-of-the-art image generation quality within seconds.

C2weakest assumption

The dual-stream decoupled sparse DiT with dynamic MoE architecture delivers the claimed quality and speed without hidden trade-offs in training cost or generalization that are not visible in the abstract.

C3one line summary

HiDream-I1 introduces a sparse DiT architecture with dual-stream processing and MoE for efficient state-of-the-art text-to-image generation, plus extensions to editing and an interactive agent.

Formal links

2 machine-checked theorem links

Cited by

23 papers in Pith

Training-Free Occluded Text Rendering via Glyph Priors and Attention-Guided Semantic Blending

Edit-GRPO: A Locality-Preserving Policy Optimization Framework for Image Editing

Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning

EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning

Emu3.5: Native Multimodal Models are World Learners

Receipt and verification

First computed	2026-05-17T23:38:47.163589Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

43df38d917593a57c2690d1eb36199ecf88174aee67352374c904b24f58931df

Aliases

arxiv: 2505.22705 · arxiv_version: 2505.22705v1 · doi: 10.48550/arxiv.2505.22705 · pith_short_12: IPPTRWIXLE5F · pith_short_16: IPPTRWIXLE5FPQTJ · pith_short_8: IPPTRWIX

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/IPPTRWIXLE5FPQTJBUPLGYMZ5T \
  | 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: 43df38d917593a57c2690d1eb36199ecf88174aee67352374c904b24f58931df

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "dd550ee1abcbe1bf090759debb645b058ecd0a633ffac7d24ab0285a932ca821",
    "cross_cats_sorted": [
      "cs.MM"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2025-05-28T17:59:15Z",
    "title_canon_sha256": "82acc6184c8cf584c2e2b30e49132316e34edf4ac9601b8e5ee655ee61c55543"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2505.22705",
    "kind": "arxiv",
    "version": 1
  }
}