Pith Number

pith:TSJHFKAD

pith:2025:TSJHFKADYEHPCHCUL7NT6I62OR

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WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

Bin Lin, Bin Zhu, Chaoran Feng, Jiaqi Liao, Kunpeng Ning, Li Yuan, Mengren Zheng, Munan Ning, Peng Jin, Weiyang Jin, Yuwei Niu

Text-to-image models struggle to apply world knowledge in generated images according to a dedicated new benchmark.

arxiv:2503.07265 v3 · 2025-03-10 · cs.CV · cs.AI · cs.CL

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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 findings reveal significant limitations in their ability to effectively integrate and apply world knowledge during image generation, highlighting critical pathways for enhancing knowledge incorporation and application in next-generation T2I models.

C2weakest assumption

That the 1000 crafted prompts and 25 subdomains provide unbiased, comprehensive tests of world knowledge integration without post-hoc selection effects or prompt engineering artifacts.

C3one line summary

Text-to-image models show significant limitations in integrating world knowledge, as measured by the new WISE benchmark and WiScore metric across 20 models.

References

61 extracted · 61 resolved · 23 Pith anchors

[1] Pixart-alpha: Fast training of diffusion transformer for photorealistic text-to-image synthe- sis, 2023 2023

[2] BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset 2025 · arXiv:2505.09568

[3] Next token prediction towards multimodal intelligence: A comprehensive survey 2024

[4] Generative pretraining from pixels 2020

[5] Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling 2025 · arXiv:2501.17811

Formal links

2 machine-checked theorem links

Cited by

35 papers in Pith

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Principled RL for Flow Matching Emerges from the Chunk-level Policy Optimization

Receipt and verification

First computed	2026-05-17T23:38:50.926726Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

9c9272a803c10ef11c545fdb3f23da74652492389699e99f44a7b54efd11347d

Aliases

arxiv: 2503.07265 · arxiv_version: 2503.07265v3 · doi: 10.48550/arxiv.2503.07265 · pith_short_12: TSJHFKADYEHP · pith_short_16: TSJHFKADYEHPCHCU · pith_short_8: TSJHFKAD

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/TSJHFKADYEHPCHCUL7NT6I62OR \
  | 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: 9c9272a803c10ef11c545fdb3f23da74652492389699e99f44a7b54efd11347d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "bf709dab7ee32b19d092e1a7de86f67f5ce30b8b494b9bf09f2aed3e12bc94aa",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CL"
    ],
    "license": "http://creativecommons.org/licenses/by-sa/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2025-03-10T12:47:53Z",
    "title_canon_sha256": "a44df9da20e1ddbd7d7d568e7762a43b8193cc99caafb92e23778ca9050dfcb9"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2503.07265",
    "kind": "arxiv",
    "version": 3
  }
}