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Ewha Womans University, Korea University College of Medicine
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Top-performing models in automated pathology rely on structured representations and hierarchical diagnostics, not just vision-language models alone.
Leading LLMs falter in Korean web-browsing tasks, achieving less than half the accuracy found in previous benchmarks.
LLMs may only account for 11-26% of high-level goal-setting in collaborations, but they exert far more influence by shaping the micro-decisions and concrete requirements that define those goals.
