MedImageEdu is a new benchmark for multi-turn multimodal radiology patient education that reveals gaps in visual grounding, safety, and handling emotional interactions in current vision-language models.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3representative citing papers
Three LLMs exhibit distinct consistency profiles in repeated exercise prescription generation, with GPT-4.1 producing unique but semantically stable outputs while Gemini 2.5 Flash achieves high similarity through text duplication.
Proposes a multi-layer framework and agent architecture that operationalizes adaptation, coherence, continuity, and agency for longitudinal health AI agents.
citing papers explorer
-
Rethinking Patient Education as Multi-turn Multi-modal Interaction
MedImageEdu is a new benchmark for multi-turn multimodal radiology patient education that reveals gaps in visual grounding, safety, and handling emotional interactions in current vision-language models.
-
Cross-Model Consistency of AI-Generated Exercise Prescriptions: A Repeated Generation Study Across Three Large Language Models
Three LLMs exhibit distinct consistency profiles in repeated exercise prescription generation, with GPT-4.1 producing unique but semantically stable outputs while Gemini 2.5 Flash achieves high similarity through text duplication.
-
A Framework for Longitudinal Health AI Agents
Proposes a multi-layer framework and agent architecture that operationalizes adaptation, coherence, continuity, and agency for longitudinal health AI agents.