Measuring the Reasoning-Action Coupling in Driving Vision-Language-Action Models through Counterfactuals
3 judges. Scored by all three judges. Only the day’s top stories get the claim check. How far stories are checked
This paper uses counterfactual interventions on four driving vision-language-action models to test whether their generated reasoning actually drives their trajectories and whether both respond to changes in the visual scene. Its tests cover reasoning-side text edits compared against camera blanking, and object removal from camera frames.
Score
0.67total under rubric v2.0
- Significance0.64
- Reader interest0.70
- Audience breadth0.52
- Practical relevance0.62
- Substantiated0.86
- Technical depth0.91
- New information0.87
- Counts against: Promotional0.04
- Counts against: Overclaim0.25
Each judge’s answer per question (0–1), their mean and spread, and what the question adds to the score (weight × mean).
| Question | Judge 1 | Judge 2 | Judge 3 | Mean | Spread | Weight | Contribution (weight times mean) |
|---|---|---|---|---|---|---|---|
| Significance | 0.65 | 0.45 | 0.82 | 0.64 | 0.37 | +0.25 | +0.160 |
| Reader interest | 0.61 | 0.60 | 0.88 | 0.70 | 0.28 | +0.20 | +0.139 |
| Audience breadth | 0.49 | 0.45 | 0.62 | 0.52 | 0.17 | +0.10 | +0.052 |
| Practical relevance | 0.64 | 0.50 | 0.72 | 0.62 | 0.22 | +0.15 | +0.093 |
| Substantiated | 0.97 | 0.72 | 0.90 | 0.86 | 0.25 | +0.10 | +0.086 |
| Technical depth | 0.98 | 0.80 | 0.96 | 0.91 | 0.18 | +0.10 | +0.091 |
| New information | 0.92 | 0.70 | 0.98 | 0.87 | 0.28 | +0.10 | +0.087 |
| Promotional | 0.05 | 0.05 | 0.01 | 0.04 | 0.04 | −0.15 | −0.006 |
| Overclaim | 0.26 | 0.30 | 0.18 | 0.25 | 0.12 | −0.15 | −0.037 |
| Sum of contributions | +0.666 | ||||||
| Claim-check penalty | 0.000 | ||||||
| Total, as published | 0.666 | ||||||
Spread is the highest minus the lowest judge answer. marks a spread above 0.40: the judges disagree, and the story is marked contested.
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