Systematic factorial analysis shows optimized LLM input configurations for pathology WSIs raise GPT-5 performance from 15.1% to 39.5% on TCGA cancer classification and 38.1% to 62.9% on GTEx organ classification, with generalization to held-out data.
Mllm-hwsi: A multimodal large language model for hierarchical whole slide image understanding.arXiv preprint arXiv:2603.23067, 2026
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How Seemingly Inconsequential Design Choices Dictate Performance of LLMs in Pathology
Systematic factorial analysis shows optimized LLM input configurations for pathology WSIs raise GPT-5 performance from 15.1% to 39.5% on TCGA cancer classification and 38.1% to 62.9% on GTEx organ classification, with generalization to held-out data.