# What is the difference between "state consistency" and "behaviour consistency" for a text world model, and which of the two papers (arXiv 2604.13824, 2610.06637) defines which notion?

- id: art_01M5MXSWDF4KTGWB27P688SR8V
- 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, T18, T20 · tags: none
- updated: 2026-10-23T17:44:09.868Z
- url: https://veyrul.com/articles/art_01M5MXSWDF4KTGWB27P688SR8V

Both IDs resolve to the described papers. arXiv 2604.13824v2 (Huang et al.) separates three things: state consistency (predicted next-state text looks like the real next-state text; what exact-match and token-F1 style training reward), functional consistency (Definition 1: the same action distribution of a given agent under predicted and real state) and behaviour consistency (its training paradigm and the BehR reward, a logged-action likelihood proxy for functional consistency), plus a task-level metric CR_pw measured by replaying the world model's actions in the real environment. arXiv 2610.06637v1 (Wang et al.) does not define "consistency" at all; its nearest notions are a predictive-sufficiency condition on the learned state and a counterfactual action-sensitivity test.

Both IDs resolve to the described papers. arXiv 2604.13824v2 (Huang et al.) separates three things: state consistency (predicted next-state text looks like the real next-state text; what exact-match and token-F1 style training reward), functional consistency (Definition 1: the same action distribution of a given agent under predicted and real state) and behaviour consistency (its training paradigm and the BehR reward, a logged-action likelihood proxy for functional consistency), plus a task-level metric CR_pw measured by replaying the world model's actions in the real environment. arXiv 2610.06637v1 (Wang et al.) does not define "consistency" at all; its nearest notions are a predictive-sufficiency condition on the learned state and a counterfactual action-sensitivity test.

Curator qualifications: Huang et al. separate state consistency (text match), functional consistency (same agent action distribution under predicted vs real state) and behaviour consistency (BehR reward).

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/2604.13824v2",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2610.06637v1",
      "note": "candidate evidence excerpts"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Both IDs resolve to the described papers. arXiv 2604.13824v2 (Huang et al.) separates three things: state consistency (predicted next-state text looks like the real next-state text; what exact-match and token-F1 style training reward), functional consistency (Definition 1: the same action distribution of a given agent under predicted and real state) and behaviour consistency (its training paradigm and the BehR reward, a logged-action likelihood proxy for functional consistency), plus a task-level metric CR_pw measured by replaying the world model's actions in the real environment. arXiv 2610.06637v1 (Wang et al.) does not define "consistency" at all; its nearest notions are a predictive-sufficiency condition on the learned state and a counterfactual action-sensitivity test. · locator: candidate evidence excerpts · source: https://arxiv.org/abs/2604.13824v2

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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