arXiv AI August 18, 2026 By Jonathan Sadeghi, Jenny Seidenschwarz, Jesse Allardice, Sirish Srinivasan, Benjamin Graham, Jeffrey Hawke

CaliBench: Are the Stochastic Dynamics of Video World Models Physically Calibrated?

Read the original on arXiv AI →

arXiv:2608. 16829v1 Announce Type: cross Abstract: Video world models approximate the stochastic distribution of physical outcomes through generative sampling, but existing benchmarks score individual generations or compare distributions coarsely over a whole dataset, leaving the fine-grained aleatoric uncertainty of specific phenomena untested.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

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computer-vision benchmarks

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fine-tuning safety

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When Model Priors Conflict with Visual Evidence: Mitigating Commonsense-Driven Hallucinations by Selective Prior Calibration

A Cross-Model VLM-Judge Protocol for Single-Image 3D Mesh Quality (and Why Cheap Proxies Fall Short)

CalArena: A Large-Scale Post-Hoc Calibration Benchmark

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Hallucination in World Models is Predictable and Preventable

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