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Plausible Pictures Failed the Global Rule
RIG-BENCH tests whether generators can infer a hidden visual rule and render a logically constrained answer across 2,000 samples.
Summary
RIG-BENCH tests whether generators can infer a hidden visual rule and render a logically constrained answer across 2,000 samples.
The benchmark spans concept, transformation, pattern-and-structure, and scenario reasoning rather than asking only whether an image matches surface events. Evaluations of unified generative models and image/video systems found a recurring gap: outputs could look locally plausible while violating the global constraint. The result is a diagnostic dataset and preprint claim, not evidence that every visual generator fails every reasoning task.
Why it matters
RIG-BENCH tests whether generators can infer a hidden visual rule and render a logically constrained answer across 2,000 samples.
Limits and context
- The benchmark spans concept, transformation, pattern-and-structure, and scenario reasoning rather than asking only whether an image matches surface events.
- The result is a diagnostic dataset and preprint claim, not evidence that every visual generator fails every reasoning task.
Key claims
RIG-BENCH tests whether generators can infer a hidden visual rule and render a logically constrained answer across 2,000 samples.
Qualification: The benchmark spans concept, transformation, pattern-and-structure, and scenario reasoning rather than asking only whether an image matches surface events.
Evidence: source-2026-09-03-015
Sources
- arXiv preprint 2609.02864arXiv · primary research
Corrections
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