REMEDY: How Far Is Video Generation from Medical Education World Models?

arXiv:2609.32460 · cs.CV · Submitted 2026-09-26 · Read on arXiv

cs.CV

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/ultralytics/ultralytics

Terminology

• Benchmark — 39× in this paper · explained in 2 episodes
• Consistency — 17× in this paper · explained in 3 episodes
• World Model — 7× in this paper · explained in 7 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Failure Modes — 4× in this paper · explained in 3 episodes
• LLM-as-a-Judge — 4× in this paper · explained in 3 episodes
• Clinical Atom Score — 3× in this paper
• Evaluation Dimensions — 3× in this paper · explained in 3 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• LLM judge — 3× in this paper · explained in 2 episodes
• Temporal consistency — 3× in this paper · explained in 2 episodes
• Total Knee Arthroplasty — 3× in this paper
• Benchmarking — 2× in this paper · explained in 4 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Minimally Invasive Spine Surgery — 2× in this paper
• Partial Knee Arthroplasty — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Cardio-Pulmonary Resuscitation — 1× in this paper
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 4 episodes
• In International Conference on Machine Learning — 1× in this paper
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Safety is Contextual, LLM-Judges Are Not: Navigating the Rigid Priors of Evaluators
• VideoPhy: Evaluating Physical Commonsense for Video Generation
• EduVQA: Towards Concept-Aware Assessment of Educational AI-Generated Videos
• MoHallBench: A Benchmark for Motion Hallucination in Video Large Language Models
• How Far Are Surgeons from Surgical World Models? A Pilot Study on Zero-shot Surgical Video Generation with Expert Assessment
• Same Verdict, Different Reasons: LLM-as-a-Judge and Clinician Disagreement on Medical Chatbot Completeness
• HumanScore: Benchmarking Human Motions in Generated Videos
• LTX-2: Efficient Joint Audio-Visual Foundation Model
• VLM Judges Can Rank but Cannot Score: Task-Dependent Uncertainty in Multimodal Evaluation
• MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation
• Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation
• Do generative video models understand physical principles?
• Cosmos World Foundation Model Platform for Physical AI
• Right Answer, Wrong Method: Shortcut Hacking Misleads the Evaluation of LLM Reasoning on Frontier Science Benchmarks
• T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation
• Bora: Biomedical Generalist Video Generation Model
• Towards Accurate Generative Models of Video: A New Metric & Challenges
• LLM Judges Have Dark Current: A Psychometric Datasheet for LLM-as-a-Judge Evaluation

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models