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20232026
most citedInvestigating the performance of Retrieval-Augmented Generation and fine-tuning for the development of AI-driven knowledge-based systems

36 citations · 49 across the 4 of their papers we have counts for

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cs.CV2026★ 1 cited

Million-scale multimodal pollen microscopy with expert-guided foundation models

András Biricz, Björn Gedda, Donát Magyar +4

Automated pollen identification from microscopy remains a bottleneck in aerobiology, palaeoecology and biodiversity monitoring, because scalable systems must generalise across spec…