A panel of LVLMs that generate, evaluate, and learn from each other's outputs improves average benchmark scores by 9 points across 15 tasks.
Learning transferable visual models from natural language supervi- sion
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Improving Large Vision and Language Models by Learning from a Panel of Peers
A panel of LVLMs that generate, evaluate, and learn from each other's outputs improves average benchmark scores by 9 points across 15 tasks.