Pith Number

pith:Y5HR3MRX

pith:2022:Y5HR3MRXMK6FSX6PMAM4S5Z6Q4

not attested not anchored not stored refs resolved

eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

Arash Vahdat, Bryan Catanzaro, Jiaming Song, Karsten Kreis, Miika Aittala, Ming-Yu Liu, Qinsheng Zhang, Samuli Laine, Seungjun Nah, Tero Karras, Timo Aila, Xun Huang, Yogesh Balaji

An ensemble of stage-specialized diffusion models improves text alignment in image synthesis at the same inference cost.

arxiv:2211.01324 v5 · 2022-11-02 · cs.CV · cs.LG

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{Y5HR3MRXMK6FSX6PMAM4S5Z6Q4}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

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

Our ensemble of diffusion models, called eDiff-I, results in improved text alignment while maintaining the same inference computation cost and preserving high visual quality, outperforming previous large-scale text-to-image diffusion models on the standard benchmark.

C2weakest assumption

The synthesis behavior qualitatively changes throughout the generation process such that early stages rely on text conditioning while later stages largely ignore it, making a single shared-parameter model suboptimal.

C3one line summary

An ensemble of stage-specialized text-to-image diffusion models improves prompt alignment over single shared-parameter models while preserving visual quality and inference speed.

References

95 extracted · 95 resolved · 11 Pith anchors

[1] V ., Du, J., Iyer, S., Pasunuru, R., et al 2021

[2] Blended latent diffusion 2022

[3] Blended diffusion for text-driven editing of natural images 2022

[4] Estimating the optimal covariance with imperfect mean in diffusion probabilistic models 2022

[5] Analytic- DPM: An analytic estimate of the optimal reverse variance in diffusion probabilistic models 2022

Formal links

2 machine-checked theorem links

Cited by

48 papers in Pith

UniEmo: Unifying Emotional Understanding and Generation with Learnable Expert Queries

FireScope: Wildfire Risk Raster Prediction with a Chain-of-Thought Oracle

NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)

Prompt Evolution for Generative AI: A Classifier-Guided Approach

DiFaReli++: Diffusion Face Relighting with Consistent Cast Shadows

Receipt and verification

First computed	2026-05-17T23:39:05.095621Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c74f1db23762bc595fcf6019c9773e8727f464891dc08adab64526d371aebe71

Aliases

arxiv: 2211.01324 · arxiv_version: 2211.01324v5 · doi: 10.48550/arxiv.2211.01324 · pith_short_12: Y5HR3MRXMK6F · pith_short_16: Y5HR3MRXMK6FSX6P · pith_short_8: Y5HR3MRX

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/Y5HR3MRXMK6FSX6PMAM4S5Z6Q4 \
  | 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: c74f1db23762bc595fcf6019c9773e8727f464891dc08adab64526d371aebe71

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6ba932880558e507ebb983d38e510f4e566f11bba98dcd82cf7a99666372929f",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2022-11-02T17:43:04Z",
    "title_canon_sha256": "e9f8d1e62e63e995eafd74d40a92cab36ae1e21fca1d6f3683a0e8e5ac675eea"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2211.01324",
    "kind": "arxiv",
    "version": 5
  }
}