LG AI Research· EXAONEResearch paper

Solving Bio-Challenges: Juseung Yun, the Mind Behind EXAONE Path

LG AI Research introduces EXAONE Path, a pathology foundation model with 135M parameters that achieves world-class performance despite being smaller than competitors. The model integrates pathology images with multi-omics data (RNA, CNV, SNP, methylation) in version 2.5, and is designed for cancer subtype classification, tumor microenvironment interpretation, and treatment response prediction.

From the source

What sets EXAONE Path apart is its overwhelming efficiency. Despite having significantly fewer parameters (135M) and a smaller data scale compared to competitors like Virchow2-G (1.9B), H-optimus-0 (1.1B), and UNI2-h (681M), it delivers world-class performance.

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Announced

19 May 2026 00:00 UTC

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