# How do robot world-model sources define action conditioning and what do they measure (video quality, value prediction, policy ranking), and which numbers support the claim that a world model can rank robot policies?

- id: art_01M5MCA0ZFW467715BR5V3DGWE
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T15, T20 · tags: none
- updated: 2026-10-23T12:38:24.470Z
- url: https://veyrul.com/articles/art_01M5MCA0ZFW467715BR5V3DGWE

Robot world models condition on low-level action vectors: a 7-D gripper delta on Bridge (Cosmos), whole-body command sequences (1XWM). Released-capability evidence for robots is narrow: Cosmos reports PSNR/SSIM/latent L2/FVD on Bridge (Predict1-7B FVD 190; Predict2.5-2B FVD 146 under the same protocol) and a ten-person preference test; 1X reports value-prediction accuracy and a predicted-vs-real success correlation shown in figures. The headline claim that a 70%-accurate world model picks the better of two policies 90% of the time (15% real gap) is stated twice by 1X (blog and report, with different wording) without a derivation in the text. The 1X challenge repo gives open baselines and a loss target but its own README warns that retrieval from training data scores well on the dev split.

Robot world models condition on low-level action vectors: a 7-D gripper delta on Bridge (Cosmos), whole-body command sequences (1XWM). Released-capability evidence for robots is narrow: Cosmos reports PSNR/SSIM/latent L2/FVD on Bridge (Predict1-7B FVD 190; Predict2.5-2B FVD 146 under the same protocol) and a ten-person preference test; 1X reports value-prediction accuracy and a predicted-vs-real success correlation shown in figures. The headline claim that a 70%-accurate world model picks the better of two policies 90% of the time (15% real gap) is stated twice by 1X (blog and report, with different wording) without a derivation in the text. The 1X challenge repo gives open baselines and a loss target but its own README warns that retrieval from training data scores well on the dev split.

Curator qualifications: Robot world models condition on low-level action vectors; released evidence narrow (PSNR/SSIM/FVD on Bridge).

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

```json
{
  "citations": [
    {
      "url": "https://www.1x.tech/1x-world-model.pdf",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://www.1x.tech/discover/redwood-ai-world-model",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://www.1x.tech/discover/1x-world-model",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2501.03575v3",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2511.00062v2",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://github.com/1x-technologies/1xgpt/tree/006973446bda975b93a7f93ac6a41e33ddccc865",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://www.1x.tech/discover/1x-world-model-sampling-challenge",
      "note": "candidate evidence excerpts"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Robot world models condition on low-level action vectors: a 7-D gripper delta on Bridge (Cosmos), whole-body command sequences (1XWM). Released-capability evidence for robots is narrow: Cosmos reports PSNR/SSIM/latent L2/FVD on Bridge (Predict1-7B FVD 190; Predict2.5-2B FVD 146 under the same protocol) and a ten-person preference test; 1X reports value-prediction accuracy and a predicted-vs-real success correlation shown in figures. The headline claim that a 70%-accurate world model picks the better of two policies 90% of the time (15% real gap) is stated twice by 1X (blog and report, with different wording) without a derivation in the text. The 1X challenge repo gives open baselines and a loss target but its own README warns that retrieval from training data scores well on the dev split. · locator: candidate evidence excerpts · source: https://www.1x.tech/1x-world-model.pdf

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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