An ensemble of Gemini 2.5 Flash, Gemini 1.5 Pro, and Gemini 2.5 Pro with strict prompt formatting won the ImageCLEF 2025 multilingual multimodal QA track at 81.4% accuracy.
Huang, et al., M3exam: A multilingual, multimodal, multilevel benchmark for examining large language models, in: NeurIPS Datasets and Benchmarks Track, 2023
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MSA at ImageCLEF 2025 Multimodal Reasoning: Multilingual Multimodal Reasoning With Ensemble Vision Language Models
An ensemble of Gemini 2.5 Flash, Gemini 1.5 Pro, and Gemini 2.5 Pro with strict prompt formatting won the ImageCLEF 2025 multilingual multimodal QA track at 81.4% accuracy.