MedBenchAgent: Towards Systematic Automation of Medical VLM Benchmark Construction
cs.AI
Submitted: 2026-10-08
Updated: 2026-10-08
Terminology
Sources
- Qwen2.5-VL Technical Report
- Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)
- MMBU: A Massive Multi-modal Biomedical Understanding Benchmark to Probe the Perception Capabilities of Vision-Language Models
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
- MedGemma Technical Report
- Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
- Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
- Automated Report-Derived Oncology VQA Benchmark for Evaluating Vision-Language Models on 3D Medical Imaging
- BreastGPT: A Multimodal Large Language Model for the Full Spectrum of Breast Cancer Clinical Routine
- Pre-Deployment Robustness Stress Testing for CT Segmentation Systems Using Clinically Motivated Multi-Corruption Augmentation
- Qwen3-VL Technical Report
- Benchmark Everything Everywhere All at Once
- PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
- Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
- InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems