# How well does GenEval agree with human raters, which settings were tuned to get that agreement, and where does it fail or stop discriminating?

- id: art_01M5NP1W1KK3Z4F03NMYRMVX92
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=metadata_checked, execution=not_run, review=unreviewed
- categories: T05, T20 · tags: none
- updated: 2026-10-24T00:47:57.485Z
- url: https://veyrul.com/articles/art_01M5NP1W1KK3Z4F03NMYRMVX92

Partially verified: the curator re-read none of the cited sources; S1 rests on the producer's pinned reading. In the authors' MTurk study (6,000 annotations over 1,200 images) GenEval agreed with humans on 83% of images versus 88% pairwise annotator agreement and 80% for a per-task thresholded CLIPScore; on 860 unanimous images agreement was 91% vs 87%. The counting confidence threshold (0.9) and the colour crop+mask step were chosen against human labels, and the paper lists holes in objects, overlapping same-type objects and non-photographic art as failures. Single-object prompts are near ceiling for all tested Stable Diffusion/IF models, and the paper notes kappa 0 there because almost all images were correct.

Partially verified: the curator re-read none of the cited sources; S1 rests on the producer's pinned reading.

In the authors' MTurk study (6,000 annotations over 1,200 images) GenEval agreed with humans on 83% of images versus 88% pairwise annotator agreement and 80% for a per-task thresholded CLIPScore; on 860 unanimous images agreement was 91% vs 87%. The counting confidence threshold (0.9) and the colour crop+mask step were chosen against human labels, and the paper lists holes in objects, overlapping same-type objects and non-photographic art as failures. Single-object prompts are near ceiling for all tested Stable Diffusion/IF models, and the paper notes kappa 0 there because almost all images were correct.

Curator qualifications: Partially verified: the curator re-read none of the cited sources; S1 rests on the producer's pinned reading. Curator GET 2026-10-23 of the sources not re-read (mechanical source evidence, not semantic verification): S1: HTTP 200, bytes differ from the producer pin.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://arxiv.org/abs/2310.11513v1",
      "note": "candidate evidence excerpts"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] In the authors' MTurk study (6,000 annotations over 1,200 images) GenEval agreed with humans on 83% of images versus 88% pairwise annotator agreement and 80% for a per-task thresholded CLIPScore; on 860 unanimous images agreement was 91% vs 87%. The counting confidence threshold (0.9) and the colour crop+mask step were chosen against human labels, and the paper lists holes in objects, overlapping same-type objects and non-photographic art as failures. Single-object prompts are near ceiling for all tested Stable Diffusion/IF models, and the paper notes kappa 0 there because almost all images were correct. · locator: candidate evidence excerpts · source: https://arxiv.org/abs/2310.11513v1

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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