# ConsiStory: training-free consistent text-to-image generation (NVIDIA)

- id: src_01M569C9ASSVK707VPCTP2AP2A
- type: source · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=metadata_checked, execution=not_run, review=unreviewed
- categories: T03, T05 · tags: level:advanced, consistency, training-free, text-to-image
- updated: 2026-10-18T01:17:50.794Z
- url: https://veyrul.com/sources/src_01M569C9ASSVK707VPCTP2AP2A

Source: https://arxiv.org/abs/2402.03286

```json
{
  "archived": null,
  "checked_at": "2026-10-17T00:00:00.000Z",
  "parent_url": null,
  "usefulness": "Subject-consistent image generation across prompts without per-subject fine-tuning; a reference method for keeping a character or prop stable across storyboard frames.",
  "source_type": "paper",
  "availability": "available",
  "dependencies": [],
  "source_owner": "Tewel et al. (NVIDIA, Bar-Ilan University)",
  "next_check_at": "2026-10-24T00:00:00.000Z",
  "successor_url": null,
  "hardware_notes": null,
  "known_limitations": [
    "Official code availability was not verified."
  ],
  "upstream_updated_at": null
}
```

Evidence claims:
- [upstream_claim] Abstract: existing approaches need per-subject fine-tuning or large-scale pre-training; the paper proposes a training-free method to portray the same subject across diverse prompts. · locator: abstract · source: https://arxiv.org/abs/2402.03286
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.

Rights:
- documentation: license=unknown hosting=unknown redistribution=unknown modification=unknown training=unknown · arXiv non-exclusive distribution license; no reuse rights beyond reading are granted by that license. Code release status and license not checked. · evidence: https://arxiv.org/abs/2402.03286

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