Pith Number

pith:4VGU4GT2

pith:2026:4VGU4GT2VH2UJ62QWMHBW3SFBK

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When Do Diffusion Models learn to Generate Multiple Objects?

Anna Rohrbach, Arnas Uselis, Iro Laina, Seong Joon Oh, Yujin Jeong

Diffusion models' multi-object generation is limited primarily by scene complexity and held-out combinations rather than imbalance, with counting difficult in low data and compositional generalization collapsing as more combinations are excluded.

arxiv:2605.00273 v2 · 2026-04-30 · cs.CV · cs.AI

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\pithnumber{4VGU4GT2VH2UJ62QWMHBW3SFBK}

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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

By training diffusion models on mosaic, we find that scene complexity plays a dominant role rather than concept imbalance, and that counting is uniquely difficult to learn in low-data regimes. Moreover, compositional generalization collapses as more concept combinations are held out during training.

C2weakest assumption

That the synthetic MOSAIC datasets and the defined regimes of concept versus compositional generalization capture the essential factors driving failures in real-world text-to-image diffusion models trained on natural image distributions.

C3one line summary

Receipt and verification

First computed	2026-06-09T02:08:43.167864Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e54d4e1a7aa9f544fb50b30e1b6e450a9c99bbca5ebd078103d5d9295c49ae52

Aliases

arxiv: 2605.00273 · arxiv_version: 2605.00273v2 · doi: 10.48550/arxiv.2605.00273 · pith_short_12: 4VGU4GT2VH2U · pith_short_16: 4VGU4GT2VH2UJ62Q · pith_short_8: 4VGU4GT2

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/4VGU4GT2VH2UJ62QWMHBW3SFBK \
  | 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: e54d4e1a7aa9f544fb50b30e1b6e450a9c99bbca5ebd078103d5d9295c49ae52

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "62e90c1b7550aaf042a0b066dcb80322649345bf39790d22c032f0eabbd4c047",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-30T22:18:33Z",
    "title_canon_sha256": "f881bbc380d7acf33c862467119c0bc3d776c56632d851eb0afbae4bae64ad09"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.00273",
    "kind": "arxiv",
    "version": 2
  }
}