EyeVQA: Benchmarking Ophthalmic Vision-Language Models from Recognition to Spatial Grounding

arXiv:2609.32352 · cs.CV, cs.AI · Submitted 2026-09-26 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-26

Updated: 2026-09-29

Code: https://github.com/PKUTHM/EyeVQA

Terminology

Benchmark — 24× in this paper · explained in 2 episodes
Grounding — 21× in this paper · explained in 3 episodes
Bounding Box — 11× in this paper
Diabetic Retinopathy — 9× in this paper
Macula Disease — 9× in this paper
Point Location — 8× in this paper
Vision-language models — 8× in this paper · explained in 2 episodes
Pathological Myopia — 5× in this paper
Vision-Language Models (VLMs) — 5× in this paper · explained in 6 episodes
Accuracy — 4× in this paper · explained in 1 episode
Benchmarking — 4× in this paper · explained in 4 episodes
Adam — 3× in this paper · explained in 2 episodes
Alignment — 2× in this paper · explained in 1 episode
Foundation Model — 2× in this paper · explained in 3 episodes
Generalization — 2× in this paper · explained in 13 episodes
Segmentation Masks — 2× in this paper · explained in 2 episodes
Verification — 2× in this paper · explained in 2 episodes
Adaptation — 1× in this paper · explained in 1 episode
Consistency — 1× in this paper · explained in 3 episodes
Core — 1× in this paper · explained in 2 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Generalizability — 1× in this paper · explained in 6 episodes
Reinforcement Learning — 1× in this paper · explained in 4 episodes
Robustness — 1× in this paper · explained in 5 episodes
Unified Framework — 1× in this paper · explained in 5 episodes
Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

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