UltraG-Bench: A Multi-task Benchmark for assessing Large Vision-Language Models on Pixel-level Evidence Grounding in Ultrasound

arXiv:2609.30928 · cs.CV, cs.AI · Submitted 2026-09-25 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-25

Updated: 2026-09-25

Code: https://github.com/zhuqh19/UltraG-Bench

Terminology

• Grounding — 40× in this paper · explained in 3 episodes
• Benchmark — 30× in this paper · explained in 2 episodes
• Accuracy — 18× in this paper · explained in 1 episode
• Semantic Understanding — 14× in this paper · explained in 2 episodes
• Segmentation Masks — 10× in this paper · explained in 2 episodes
• Foundation Model — 9× in this paper · explained in 3 episodes
• Consistency — 6× in this paper · explained in 3 episodes
• Visual Grounding — 6× in this paper · explained in 2 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Adam — 4× in this paper · explained in 2 episodes
• Vision-language models — 4× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Multimodal Reasoning — 2× in this paper · explained in 5 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Visual Reasoning — 1× in this paper · explained in 2 episodes
• Modality Gap — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Task Planning — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• PathVQA: 30000+ Questions for Medical Visual Question Answering
• UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation
• Chest ImaGenome Dataset for Clinical Reasoning
• OpenAI GPT-5 System Card
• Qwen3-VL Technical Report
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• MiniCPM-V: A GPT-4V Level MLLM on Your Phone
• MedGemma Technical Report
• MMOTU: A Multi-Modality Ovarian Tumor Ultrasound Image Dataset for Unsupervised Cross-Domain Semantic Segmentation

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