Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains
We introduce Sci-VBench, a comprehensive benchmark for evaluating knowledge- and reasoning-intensive video generation across scientific domains. It contains 1,253 expert-annotated examples spanning 60 subjects across four core disciplines: Natural Science, Healthcare, Humanities & Social Sciences, and Engineering. Each example requires models to generate temporally rich videos that demand scientific reasoning and knowledge-grounded synthesis, going beyond surface-level visual plausibility. We fu
Record details
Published: 9 August 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Healthcare
Retrieved: 11 August 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains
arXiv cs.AI · 10 August 2026
RibAssist 3D: Biplanar Rib-Fracture Detection, Addressing, and Selective 3D Localization from CT-Derived Projections
HuggingFace Daily Papers · 9 August 2026
Decoding-Level Taboo: A Diagnostic Stress Test for LLM Robustness
HuggingFace Daily Papers · 9 August 2026
SHRIMP: Iterative Refinement of Robot Task Plans
arXiv cs.HC · 9 August 2026
Wearing Trust: How Older Adults Calibrate Reliance on Health Wearables Through Bodily Experience and Everyday Use
arXiv cs.HC · 9 August 2026
Decoding Phenotypes: A Framework for Fusing Genomic Language Models and Neuroimaging
arXiv cs.LG · 9 August 2026
How to cite this record
ethics.ai (9 August 2026), “Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains,” evidence record 17974, https://ethics.ai/record/17974 (originally published by HuggingFace Daily Papers).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.